Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,rad...Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,radiomics,and multimodal data integration,AI has achieved diagnostic parity with expert cli-nicians in endoscopic image analysis(e.g.,early gastric cancer detection,colorectal polyp identification)and non-invasive assessment of liver pathologies(e.g.,fibrosis staging,fatty liver typing)while demonstrating utility in personalized care scenarios such as predicting hepatocellular carcinoma recurrence and opti-mizing inflammatory bowel disease treatment responses.Despite these advance-ments challenges persist including limited model generalization due to frag-mented datasets,algorithmic limitations in rare conditions(e.g.,pediatric liver diseases)caused by insufficient training data,and unresolved ethical issues related to bias,accountability,and patient privacy.Mitigation strategies involve constructing standardized multicenter databases,validating AI tools through prospective trials,leveraging federated learning to address data scarcity,and de-veloping interpretable systems(e.g.,attention heatmap visualization)to enhance clinical trust.Integrating generative AI,digital twin technologies,and establishing unified ethical/regulatory frameworks will accelerate AI adoption in primary care and foster equitable healthcare access while interdisciplinary collaboration and evidence-based implementation remain critical for realizing AI’s potential to redefine precision care for digestive disorders,improve global health outcomes,and reshape healthcare equity.展开更多
Artificial intelligence(AI)has emerged as a transformative tool in the diagnosis and management of gastrointestinal(GI)and liver diseases.In clinical practice AI consists of overlapping technologies such as machine le...Artificial intelligence(AI)has emerged as a transformative tool in the diagnosis and management of gastrointestinal(GI)and liver diseases.In clinical practice AI consists of overlapping technologies such as machine learning(ML),deep lear-ning,natural language processing,computer vision,and generative AI.ML is a computer learning system that can provide insight into disease risk factors and phenotypes.Deep learning is an advanced and complex form of ML,structured with different levels of specific algorithms known as convolutional neural net-works that can rapidly and accurately process unstructured,high-dimensional data,such as texts,images,and waveforms.Natural language processing is dedi-cated to facilitating interactions between computers and humans using natural language and helps to analyze,understand,and derive actionable information from unstructured healthcare data,including electronic health records,clinical notes,medical literature,and patient-generated content.Computer vision focuses on enabling computers to see and interpret images and videos and serves as an augmentation tool for endoscopists,improving accuracy and decreasing procedu-ral time.Generative AI is capable of creating new forms of content by learning from a large body of data in the form of text,audio,images,or video and includes large language models.AI has been used in several GI diseases such as esopha-geal neoplasia,gastric cancer,Helicobacter pylori infection,gastritis,GI stromal tumors,colorectal polyps,inflammatory bowel disease,irritable bowel syndrome,GI bleeding,and pancreatobiliary diseases.The potential applications of AI in liver diseases encompass a variety of conditions such as liver masses,metabolic dysfunction-associated steatotic liver disease,viral hepatitis,cirrhosis,and liver transplantation.This review discussed the common terminologies and the current status of AI in gastroenterology and hepatology,exploring its applications and ethical issues.展开更多
Genomic medicine has evolved significantly,merging centuries of scientific progress with modern molecular biology and clinical care.It utilizes knowledge of the human genome to enhance disease prevention,diagnosis,tre...Genomic medicine has evolved significantly,merging centuries of scientific progress with modern molecular biology and clinical care.It utilizes knowledge of the human genome to enhance disease prevention,diagnosis,treatment,and potential reversal.Genomic medicine in hepatology is particularly promising due to the crucial role of the liver in several metabolic processes and its association with diseases such as metabolic dysfunction-associated steatotic liver disease,type 2 diabetes mellitus,liver cirrhosis,and cardiovascular conditions.The mid-20th century witnessed a paradigm shift in medicine,marked by the emergence of molecular biology,which enabled a deeper understanding of gene expression and regulation.This connection between basic science and clinical practice has enhanced our knowledge of the role of gene-environment interactions in the onset and progression of liver diseases.In Latin America,including Mexico,with its genetically diverse and admixed populations,genomic medicine provides a foundation for personalized and culturally relevant health strategies.This review highlights the need for genomic medicine,examining its historical evolution,integration into hepatology in Mexico,and its potential applications in the prevention of chronic diseases.It emphasizes the importance of training in genomic literacy and interdisciplinary education in medical training,particularly in the field of hepatology,with a focus on genomic medicine expertise.展开更多
With the rapid development of artificial intelligence(AI)technology,multimodal data integration has become an important means to improve the accuracy of diagnosis and treatment in gastroenterology and hepatology.This ...With the rapid development of artificial intelligence(AI)technology,multimodal data integration has become an important means to improve the accuracy of diagnosis and treatment in gastroenterology and hepatology.This article systematically reviews the latest progress of multimodal AI technology in the diagnosis,treatment,and decision-making for gastrointestinal tumors,functional gastrointestinal diseases,and liver diseases,focusing on the innovative applications of endoscopic image AI,pathological section AI,multi-omics data fusion models,and wearable devices combined with natural language processing.Multimodal AI can significantly improve the accuracy of early diagnosis and the efficiency of individualized treatment planning by integrating imaging,pathological data,molecular,and clinical phenotypic data.However,current AI technologies still face challenges such as insufficient data standardization,limited generalization of models,and ethical compliance.This paper proposes solutions,such as the establishment of cross-center data sharing platform,the development of federated learning framework,and the formulation of ethical norms,and looks forward to the application prospect of multimodal large-scale models in the disease management process.This review provides theoretical basis and practical guidance for promoting the clinical translation of AI technology in the field of gastroenterology and hepatology.展开更多
Hepatology encompasses various aspects,such as metabolic-associated fatty liver disease,viral hepatitis,alcoholic liver disease,liver cirrhosis,liver failure,liver tumors,and liver transplantation.The global epidemiol...Hepatology encompasses various aspects,such as metabolic-associated fatty liver disease,viral hepatitis,alcoholic liver disease,liver cirrhosis,liver failure,liver tumors,and liver transplantation.The global epidemiological situation of liver diseases is grave,posing a substantial threat to human health and quality of life.Characterized by high incidence and mortality rates,liver diseases have emerged as a prominent global public health concern.In recent years,the rapid advan-cement of artificial intelligence(AI),deep learning,and radiomics has transfor-med medical research and clinical practice,demonstrating considerable potential in hepatology.AI is capable of automatically detecting abnormal cells in liver tissue sections,enhancing the accu-racy and efficiency of pathological diagnosis.Deep learning models are able to extract features from computed tomography and magnetic resonance imaging images to facilitate liver disease classification.Machine learning models are capable of integrating clinical data to forecast disease progression and treatment responses,thus supporting clinical decision-making for personalized medicine.Through the analysis of imaging data,laboratory results,and genomic information,AI can assist in diagnosis,forecast disease progression,and optimize treatment plans,thereby improving clinical outcomes for liver disease patients.This minireview intends to comprehensively summarize the state-of-the-art theories and applications of AI in hepatology,explore the opportunities and challenges it presents in clinical practice,basic research,and translational medicine,and propose future research directions to guide the advancement of hepatology and ultimately improve patient outcomes.展开更多
Artificial intelligence(AI)is an umbrella term used to describe a cluster of interrelated fields.Machine learning(ML)refers to a model that learns from past data to predict future data.Medicine and particularly gastro...Artificial intelligence(AI)is an umbrella term used to describe a cluster of interrelated fields.Machine learning(ML)refers to a model that learns from past data to predict future data.Medicine and particularly gastroenterology and hepatology,are data-rich fields with extensive data repositories,and therefore fruitful ground for AI/ML-based software applications.In this study,we comprehensively review the current applications of AI/ML-based models in these fields and the opportunities that arise from their application.Specifically,we refer to the applications of AI/ML-based models in prevention,diagnosis,management,and prognosis of gastrointestinal bleeding,inflammatory bowel diseases,gastrointestinal premalignant and malignant lesions,other nonmalignant gastrointestinal lesions and diseases,hepatitis B and C infection,chronic liver diseases,hepatocellular carcinoma,cholangiocarcinoma,and primary sclerosing cholangitis.At the same time,we identify the major challenges that restrain the widespread use of these models in healthcare in an effort to explore ways to overcome them.Notably,we elaborate on the concerns regarding intrinsic biases,data protection,cybersecurity,intellectual property,liability,ethical challenges,and transparency.Even at a slower pace than anticipated,AI is infiltrating the healthcare industry.AI in healthcare will become a reality,and every physician will have to engage with it by necessity.展开更多
Originally proposed by John McCarthy in 1955,artificial intelligence(AI)has achieved a breakthrough and revolutionized the processing methods of clinical medicine with the increasing workloads of medical records and d...Originally proposed by John McCarthy in 1955,artificial intelligence(AI)has achieved a breakthrough and revolutionized the processing methods of clinical medicine with the increasing workloads of medical records and digital images.Doctors are paying attention to AI technologies for various diseases in the fields of gastroenterology and hepatology.This review will illustrate AI technology procedures for medical image analysis,including data processing,model establishment,and model validation.Furthermore,we will summarize AI applications in endoscopy,radiology,and pathology,such as detecting and evaluating lesions,facilitating treatment,and predicting treatment response and prognosis with excellent model performance.The current challenges for AI in clinical application include potential inherent bias in retrospective studies that requires larger samples for validation,ethics and legal concerns,and the incomprehensibility of the output results.Therefore,doctors and researchers should cooperate to address the current challenges and carry out further investigations to develop more accurate AI tools for improved clinical applications.展开更多
Single incision laparoscopy(SIL) has become an emerging technology aiming at a further reduction of abdominal wall trauma in minimally invasive surgery. Available data is encouraging for the safe application of standa...Single incision laparoscopy(SIL) has become an emerging technology aiming at a further reduction of abdominal wall trauma in minimally invasive surgery. Available data is encouraging for the safe application of standardized SIL in a wide range of procedures in gastroenterology and hepatology. Compared to technically simple SIL procedures, the merit of SIL in advanced surgeries, such as liver or colorectal interventions, compared to conventional laparsocopy is self-evident without any doubt. SIL has already passed the learning curve and is routinely utilized in expert centers. This minimized approach has allowed to enter a new era of surgical management that can not be acceded without a fruitful combination of prudent training, consistent day-to-day work and enthusiastic motivation for technical innovations. Both, basic and novel technical specifics as well as particular procedures are described herein. The focus is on the most important surgical interventions in gastroenterology and aims at reviewingthe current literature and shares our experience in a high volume center.展开更多
After three rounds of rigorous evaluation of core journals in gastroenterology andhepatology conducted by the Reference Citation Analysis (RCA) editorial team ofBaishideng Publishing Group (Baishideng), the RCA databa...After three rounds of rigorous evaluation of core journals in gastroenterology andhepatology conducted by the Reference Citation Analysis (RCA) editorial team ofBaishideng Publishing Group (Baishideng), the RCA database of Baishidengofficially released the 2022 Journal Article Influence Index (2022 JAII) of 101 corejournals in gastroenterology and hepatology, for the first time. The list of 101 corejournals can be found at: https://www.referencecitationanalysis.com/Search-Journal. Among them, the highest 2022 JAII is 48.014 and the lowest is 3.900. Thisarticle highlights the top 20 journals, describes the calculation method for the 2022JAII, the evaluation process, and the inclusion principles for journals in the RCA.These steps are the underpinning of the RCA’s empirical journal academicevaluation service by which the digital platform addresses the needs of authors toselect reliable journals for submission, readers to select high-quality literature forreading, and editors to track their own journal citation performance. As such, theRCA core journal list will serve as a useful Find-a-Journal tool. Any interestedparty is welcome to use this journal list and recommend it to their peers.展开更多
Gastroenterologists have long been spearheading the care of patients with various forms of liver disease.The diagnosis and management of liver disease has traditionally been a combination of clinical,laboratory,and im...Gastroenterologists have long been spearheading the care of patients with various forms of liver disease.The diagnosis and management of liver disease has traditionally been a combination of clinical,laboratory,and imaging findings coupled with percutaneous and intravascular procedures with endoscopy largely limited to screening for and therapy of esophageal and gastric varices.As the applications of diagnostic and therapeutic endoscopic ultrasound(EUS)have evolved,it has found a particular niche within hepatology now coined.Here we discuss several EUS-guided procedures such as liver biopsy,shear wave elastography,direct portal pressure measurement,paracentesis,as well as EUSguided therapies for variceal hemorrhage.展开更多
In late 2019,reports arose of a new respiratory disease in China,identified as a novel coronavirus,severe acute respiratory syndrome coronavirus 2.The World Health Organisation named the disease caused by the virus‘c...In late 2019,reports arose of a new respiratory disease in China,identified as a novel coronavirus,severe acute respiratory syndrome coronavirus 2.The World Health Organisation named the disease caused by the virus‘coronavirus disease 2019(COVID-19)’.It was declared a pandemic in early 2020,after the disease rapidly spread across the world.COVID-19 has not only resulted in substantial morbidity and mortality but also significantly impacted healthcare service provision and training across all medical specialties with gastroenterology and Hepatology services being no exception.Internationally,most,if not all‘nonurgent’services have been placed on hold during surges of infections.As a result there have been delayed diagnoses,procedures,and surgeries which will undoubtedly result in increased morbidity and mortality.Outpatient services have been converted to remote consultations where possible in many countries.Trainees have been redeployed to help care for COVID-19 patients in other settings,resulting in disruption to their training-particularly endoscopy and outpatient clinics.This has led to significant anxiety amongst trainees,and risks prolongation of training.It is of the utmost importance to develop strategies that continue to support COVID-19-related service provision,whilst also supporting existing and future gastroenterology and Hepatology services and training.Changes to healthcare provision during the pandemic have generated new and improved frameworks of service and training delivery,which can be adopted in the post-COVID-19 world,leading to enhanced patient care.展开更多
The World Journal of Hepatology(WJH)was launched in October 2009.It mainly publishes articles reporting research findings in the field of hepatology,covering a wide range of topics,including viral hepatitis B and C,no...The World Journal of Hepatology(WJH)was launched in October 2009.It mainly publishes articles reporting research findings in the field of hepatology,covering a wide range of topics,including viral hepatitis B and C,non-alcoholic fatty liver disease,alcoholic liver disease,autoimmune and chronic cholestatic liver disease,drug-induced liver injury,cirrhosis,liver failure,hepatocellular carcinoma,coronavirus disease 2019-related liver conditions,etc.As of December 31,2020,the WJH has published 1349 articles,among which,the total cites is 18995 and the average cites per article is 14.In celebrating the New Year,we are pleased to share with you special a New Year’s greeting from the WJH Editors-in-Chief,along with a detailed overview of the journal’s submission,peer review and publishing metrics from 2020.In all,we are appreciative for the substantive support and submissions from authors worldwide,and the dedicated efforts and expertise provided by our invited reviewers and editorial board members.展开更多
It is increasingly recognised that collecting patient reported outcome measures(PROMs)data is an important part of healthcare and should be considered alongside traditional clinical assessments.As part of a more holis...It is increasingly recognised that collecting patient reported outcome measures(PROMs)data is an important part of healthcare and should be considered alongside traditional clinical assessments.As part of a more holistic view of healthcare provision,there has been an increased drive to implement PROM collection as part of routine clinical care in hepatology.This drive has resulted in an increase in the number of PROMs currently developed to be used in various liver conditions.However,the development and validation of a new PROM is time-consuming and costly.Therefore,before deciding to develop a new PROM,researchers should consider identifying existing PROMs to assess their appropriateness and,if necessary,make adaptations to existing PROMs to ensure their rigour when used with the target population.Little is written in the literature on how to identify and adapt the existing PROMs in hepatology.This article aims to provide a summary of the current literature and guidance regarding identifying and adapting existing PROMs in clinical practice.展开更多
近日,重庆医科大学感染性疾病分子生物学教育部重点实验室在国际肝脏病学领域顶级期刊HEPATOLOGY(影响因子:14.079)在线发表了题为"A functional variant in UBE2L3 contributes to HBV infection and maintains cccDNA stability ...近日,重庆医科大学感染性疾病分子生物学教育部重点实验室在国际肝脏病学领域顶级期刊HEPATOLOGY(影响因子:14.079)在线发表了题为"A functional variant in UBE2L3 contributes to HBV infection and maintains cccDNA stability by inducing degradation of APOBEC3A protein"研究成果。周莉副教授、任吉华博士和博士研究生程胜桃为本篇文章的第一作者,陈娟研究员和黄爱龙教授为共同通讯作者。这是数月来,该杂志又一次发表课题组相关研究工作。展开更多
BACKGROUND Accurate assessment of the quality of academic journals is of great significance.While Journal Impact Factor(JIF),calculated by Clarivate and based upon the Web of Science literature database,and CiteScore(...BACKGROUND Accurate assessment of the quality of academic journals is of great significance.While Journal Impact Factor(JIF),calculated by Clarivate and based upon the Web of Science literature database,and CiteScore(CS),developed by Elseiver and based upon the Scopus database,have enjoyed high uptake worldwide,efforts continue towards creation of other scientometric indexes that will provide evergreater qualitative insights into journal impact.Such efforts have yielded the newly-launched Journal Article Influence Index(JAII),which is based on the Reference Citation Analysis(RCA)database,an open multidisciplinary citation analysis database based on artificial intelligence technology.AIM To evaluate and summarize the similarities and differences between JAII and JIF/CS as journal evaluation indicators,and provide an intuitive method for visual representation of the related data.METHODS We searched the Journal Citation Reports to obtain the 2021 JIF list,downloaded the CS list updated in July on the Scopus website,and collected the comprehensive list of 2022 JAIIs from the RCA database(www.referencecitationanalysis.com).RESULTS Our research results revealed that by breaking through the time limit of mainstream journalevaluation methods, the JAII is able to perform well in data reliability, establishing its benefit as acomplementary scientometric index to JIF and CS.CONCLUSIONJAII provides comprehensive assessment of the quality and performance of journals.展开更多
BACKGROUND Although coronavirus disease 2019(COVID-19)presents primarily as a lower respiratory tract infection,increasing data suggests multiorgan,including the gastrointestinal(GI)tract and liver,involvement in pati...BACKGROUND Although coronavirus disease 2019(COVID-19)presents primarily as a lower respiratory tract infection,increasing data suggests multiorgan,including the gastrointestinal(GI)tract and liver,involvement in patients who are infected by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).AIM To provide a comprehensive overview of COVID-19 in gastroenterology and hepatology.METHODS Relevant studies on COVID-19 related to the study aim were undertaken through a literature search to synthesize the extracted data.RESULTS We found that digestive symptoms and liver injury are not uncommon in patients with COVID-19 and varies in different individuals.The most common GI symptoms reported are diarrhea,nausea,vomiting,and abdominal discomfort.Other atypical GI symptoms,such as loss of smell and taste and GI bleeding,have also been reported along with the evolvement of COVID-19.Liver chemistry abnormalities mainly include elevation of aspartate transferase,alanine transferase,and total bilirubin.It is postulated to be related to the binding of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)virus to the angiotensin converting enzyme-2 receptor located on several different human cells.CONCLUSION Standardized criteria should be established for diagnosis and grading of the severity of GI symptoms in COVID-19 patients.Gastroenterology and hepatology in special populations,such as children and elderly,should be the focus of further research.Future long-term data regarding GI symptoms should not be overlooked.展开更多
基金Supported by the Natural Science Foundation of Jilin Province,No.YDZJ202401182ZYTSJilin Provincial Key Laboratory of Precision Infectious Diseases,No.20200601011JCJilin Provincial Engineering Laboratory of Precision Prevention and Control for Common Diseases,Jilin Province Development and Reform Commission,No.2022C036.
文摘Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,radiomics,and multimodal data integration,AI has achieved diagnostic parity with expert cli-nicians in endoscopic image analysis(e.g.,early gastric cancer detection,colorectal polyp identification)and non-invasive assessment of liver pathologies(e.g.,fibrosis staging,fatty liver typing)while demonstrating utility in personalized care scenarios such as predicting hepatocellular carcinoma recurrence and opti-mizing inflammatory bowel disease treatment responses.Despite these advance-ments challenges persist including limited model generalization due to frag-mented datasets,algorithmic limitations in rare conditions(e.g.,pediatric liver diseases)caused by insufficient training data,and unresolved ethical issues related to bias,accountability,and patient privacy.Mitigation strategies involve constructing standardized multicenter databases,validating AI tools through prospective trials,leveraging federated learning to address data scarcity,and de-veloping interpretable systems(e.g.,attention heatmap visualization)to enhance clinical trust.Integrating generative AI,digital twin technologies,and establishing unified ethical/regulatory frameworks will accelerate AI adoption in primary care and foster equitable healthcare access while interdisciplinary collaboration and evidence-based implementation remain critical for realizing AI’s potential to redefine precision care for digestive disorders,improve global health outcomes,and reshape healthcare equity.
文摘Artificial intelligence(AI)has emerged as a transformative tool in the diagnosis and management of gastrointestinal(GI)and liver diseases.In clinical practice AI consists of overlapping technologies such as machine learning(ML),deep lear-ning,natural language processing,computer vision,and generative AI.ML is a computer learning system that can provide insight into disease risk factors and phenotypes.Deep learning is an advanced and complex form of ML,structured with different levels of specific algorithms known as convolutional neural net-works that can rapidly and accurately process unstructured,high-dimensional data,such as texts,images,and waveforms.Natural language processing is dedi-cated to facilitating interactions between computers and humans using natural language and helps to analyze,understand,and derive actionable information from unstructured healthcare data,including electronic health records,clinical notes,medical literature,and patient-generated content.Computer vision focuses on enabling computers to see and interpret images and videos and serves as an augmentation tool for endoscopists,improving accuracy and decreasing procedu-ral time.Generative AI is capable of creating new forms of content by learning from a large body of data in the form of text,audio,images,or video and includes large language models.AI has been used in several GI diseases such as esopha-geal neoplasia,gastric cancer,Helicobacter pylori infection,gastritis,GI stromal tumors,colorectal polyps,inflammatory bowel disease,irritable bowel syndrome,GI bleeding,and pancreatobiliary diseases.The potential applications of AI in liver diseases encompass a variety of conditions such as liver masses,metabolic dysfunction-associated steatotic liver disease,viral hepatitis,cirrhosis,and liver transplantation.This review discussed the common terminologies and the current status of AI in gastroenterology and hepatology,exploring its applications and ethical issues.
文摘Genomic medicine has evolved significantly,merging centuries of scientific progress with modern molecular biology and clinical care.It utilizes knowledge of the human genome to enhance disease prevention,diagnosis,treatment,and potential reversal.Genomic medicine in hepatology is particularly promising due to the crucial role of the liver in several metabolic processes and its association with diseases such as metabolic dysfunction-associated steatotic liver disease,type 2 diabetes mellitus,liver cirrhosis,and cardiovascular conditions.The mid-20th century witnessed a paradigm shift in medicine,marked by the emergence of molecular biology,which enabled a deeper understanding of gene expression and regulation.This connection between basic science and clinical practice has enhanced our knowledge of the role of gene-environment interactions in the onset and progression of liver diseases.In Latin America,including Mexico,with its genetically diverse and admixed populations,genomic medicine provides a foundation for personalized and culturally relevant health strategies.This review highlights the need for genomic medicine,examining its historical evolution,integration into hepatology in Mexico,and its potential applications in the prevention of chronic diseases.It emphasizes the importance of training in genomic literacy and interdisciplinary education in medical training,particularly in the field of hepatology,with a focus on genomic medicine expertise.
文摘With the rapid development of artificial intelligence(AI)technology,multimodal data integration has become an important means to improve the accuracy of diagnosis and treatment in gastroenterology and hepatology.This article systematically reviews the latest progress of multimodal AI technology in the diagnosis,treatment,and decision-making for gastrointestinal tumors,functional gastrointestinal diseases,and liver diseases,focusing on the innovative applications of endoscopic image AI,pathological section AI,multi-omics data fusion models,and wearable devices combined with natural language processing.Multimodal AI can significantly improve the accuracy of early diagnosis and the efficiency of individualized treatment planning by integrating imaging,pathological data,molecular,and clinical phenotypic data.However,current AI technologies still face challenges such as insufficient data standardization,limited generalization of models,and ethical compliance.This paper proposes solutions,such as the establishment of cross-center data sharing platform,the development of federated learning framework,and the formulation of ethical norms,and looks forward to the application prospect of multimodal large-scale models in the disease management process.This review provides theoretical basis and practical guidance for promoting the clinical translation of AI technology in the field of gastroenterology and hepatology.
文摘Hepatology encompasses various aspects,such as metabolic-associated fatty liver disease,viral hepatitis,alcoholic liver disease,liver cirrhosis,liver failure,liver tumors,and liver transplantation.The global epidemiological situation of liver diseases is grave,posing a substantial threat to human health and quality of life.Characterized by high incidence and mortality rates,liver diseases have emerged as a prominent global public health concern.In recent years,the rapid advan-cement of artificial intelligence(AI),deep learning,and radiomics has transfor-med medical research and clinical practice,demonstrating considerable potential in hepatology.AI is capable of automatically detecting abnormal cells in liver tissue sections,enhancing the accu-racy and efficiency of pathological diagnosis.Deep learning models are able to extract features from computed tomography and magnetic resonance imaging images to facilitate liver disease classification.Machine learning models are capable of integrating clinical data to forecast disease progression and treatment responses,thus supporting clinical decision-making for personalized medicine.Through the analysis of imaging data,laboratory results,and genomic information,AI can assist in diagnosis,forecast disease progression,and optimize treatment plans,thereby improving clinical outcomes for liver disease patients.This minireview intends to comprehensively summarize the state-of-the-art theories and applications of AI in hepatology,explore the opportunities and challenges it presents in clinical practice,basic research,and translational medicine,and propose future research directions to guide the advancement of hepatology and ultimately improve patient outcomes.
文摘Artificial intelligence(AI)is an umbrella term used to describe a cluster of interrelated fields.Machine learning(ML)refers to a model that learns from past data to predict future data.Medicine and particularly gastroenterology and hepatology,are data-rich fields with extensive data repositories,and therefore fruitful ground for AI/ML-based software applications.In this study,we comprehensively review the current applications of AI/ML-based models in these fields and the opportunities that arise from their application.Specifically,we refer to the applications of AI/ML-based models in prevention,diagnosis,management,and prognosis of gastrointestinal bleeding,inflammatory bowel diseases,gastrointestinal premalignant and malignant lesions,other nonmalignant gastrointestinal lesions and diseases,hepatitis B and C infection,chronic liver diseases,hepatocellular carcinoma,cholangiocarcinoma,and primary sclerosing cholangitis.At the same time,we identify the major challenges that restrain the widespread use of these models in healthcare in an effort to explore ways to overcome them.Notably,we elaborate on the concerns regarding intrinsic biases,data protection,cybersecurity,intellectual property,liability,ethical challenges,and transparency.Even at a slower pace than anticipated,AI is infiltrating the healthcare industry.AI in healthcare will become a reality,and every physician will have to engage with it by necessity.
基金Zhejiang Medical and Health Science and Technology Project,No.2019321842National Natural Science Foundation of China,No.81827804Zhejiang Clinical Research Center of Minimally Invasive Diagnosis and Treatment of Abdominal Diseases,No.2018E50003.
文摘Originally proposed by John McCarthy in 1955,artificial intelligence(AI)has achieved a breakthrough and revolutionized the processing methods of clinical medicine with the increasing workloads of medical records and digital images.Doctors are paying attention to AI technologies for various diseases in the fields of gastroenterology and hepatology.This review will illustrate AI technology procedures for medical image analysis,including data processing,model establishment,and model validation.Furthermore,we will summarize AI applications in endoscopy,radiology,and pathology,such as detecting and evaluating lesions,facilitating treatment,and predicting treatment response and prognosis with excellent model performance.The current challenges for AI in clinical application include potential inherent bias in retrospective studies that requires larger samples for validation,ethics and legal concerns,and the incomprehensibility of the output results.Therefore,doctors and researchers should cooperate to address the current challenges and carry out further investigations to develop more accurate AI tools for improved clinical applications.
文摘Single incision laparoscopy(SIL) has become an emerging technology aiming at a further reduction of abdominal wall trauma in minimally invasive surgery. Available data is encouraging for the safe application of standardized SIL in a wide range of procedures in gastroenterology and hepatology. Compared to technically simple SIL procedures, the merit of SIL in advanced surgeries, such as liver or colorectal interventions, compared to conventional laparsocopy is self-evident without any doubt. SIL has already passed the learning curve and is routinely utilized in expert centers. This minimized approach has allowed to enter a new era of surgical management that can not be acceded without a fruitful combination of prudent training, consistent day-to-day work and enthusiastic motivation for technical innovations. Both, basic and novel technical specifics as well as particular procedures are described herein. The focus is on the most important surgical interventions in gastroenterology and aims at reviewingthe current literature and shares our experience in a high volume center.
文摘After three rounds of rigorous evaluation of core journals in gastroenterology andhepatology conducted by the Reference Citation Analysis (RCA) editorial team ofBaishideng Publishing Group (Baishideng), the RCA database of Baishidengofficially released the 2022 Journal Article Influence Index (2022 JAII) of 101 corejournals in gastroenterology and hepatology, for the first time. The list of 101 corejournals can be found at: https://www.referencecitationanalysis.com/Search-Journal. Among them, the highest 2022 JAII is 48.014 and the lowest is 3.900. Thisarticle highlights the top 20 journals, describes the calculation method for the 2022JAII, the evaluation process, and the inclusion principles for journals in the RCA.These steps are the underpinning of the RCA’s empirical journal academicevaluation service by which the digital platform addresses the needs of authors toselect reliable journals for submission, readers to select high-quality literature forreading, and editors to track their own journal citation performance. As such, theRCA core journal list will serve as a useful Find-a-Journal tool. Any interestedparty is welcome to use this journal list and recommend it to their peers.
文摘Gastroenterologists have long been spearheading the care of patients with various forms of liver disease.The diagnosis and management of liver disease has traditionally been a combination of clinical,laboratory,and imaging findings coupled with percutaneous and intravascular procedures with endoscopy largely limited to screening for and therapy of esophageal and gastric varices.As the applications of diagnostic and therapeutic endoscopic ultrasound(EUS)have evolved,it has found a particular niche within hepatology now coined.Here we discuss several EUS-guided procedures such as liver biopsy,shear wave elastography,direct portal pressure measurement,paracentesis,as well as EUSguided therapies for variceal hemorrhage.
文摘In late 2019,reports arose of a new respiratory disease in China,identified as a novel coronavirus,severe acute respiratory syndrome coronavirus 2.The World Health Organisation named the disease caused by the virus‘coronavirus disease 2019(COVID-19)’.It was declared a pandemic in early 2020,after the disease rapidly spread across the world.COVID-19 has not only resulted in substantial morbidity and mortality but also significantly impacted healthcare service provision and training across all medical specialties with gastroenterology and Hepatology services being no exception.Internationally,most,if not all‘nonurgent’services have been placed on hold during surges of infections.As a result there have been delayed diagnoses,procedures,and surgeries which will undoubtedly result in increased morbidity and mortality.Outpatient services have been converted to remote consultations where possible in many countries.Trainees have been redeployed to help care for COVID-19 patients in other settings,resulting in disruption to their training-particularly endoscopy and outpatient clinics.This has led to significant anxiety amongst trainees,and risks prolongation of training.It is of the utmost importance to develop strategies that continue to support COVID-19-related service provision,whilst also supporting existing and future gastroenterology and Hepatology services and training.Changes to healthcare provision during the pandemic have generated new and improved frameworks of service and training delivery,which can be adopted in the post-COVID-19 world,leading to enhanced patient care.
文摘The World Journal of Hepatology(WJH)was launched in October 2009.It mainly publishes articles reporting research findings in the field of hepatology,covering a wide range of topics,including viral hepatitis B and C,non-alcoholic fatty liver disease,alcoholic liver disease,autoimmune and chronic cholestatic liver disease,drug-induced liver injury,cirrhosis,liver failure,hepatocellular carcinoma,coronavirus disease 2019-related liver conditions,etc.As of December 31,2020,the WJH has published 1349 articles,among which,the total cites is 18995 and the average cites per article is 14.In celebrating the New Year,we are pleased to share with you special a New Year’s greeting from the WJH Editors-in-Chief,along with a detailed overview of the journal’s submission,peer review and publishing metrics from 2020.In all,we are appreciative for the substantive support and submissions from authors worldwide,and the dedicated efforts and expertise provided by our invited reviewers and editorial board members.
文摘It is increasingly recognised that collecting patient reported outcome measures(PROMs)data is an important part of healthcare and should be considered alongside traditional clinical assessments.As part of a more holistic view of healthcare provision,there has been an increased drive to implement PROM collection as part of routine clinical care in hepatology.This drive has resulted in an increase in the number of PROMs currently developed to be used in various liver conditions.However,the development and validation of a new PROM is time-consuming and costly.Therefore,before deciding to develop a new PROM,researchers should consider identifying existing PROMs to assess their appropriateness and,if necessary,make adaptations to existing PROMs to ensure their rigour when used with the target population.Little is written in the literature on how to identify and adapt the existing PROMs in hepatology.This article aims to provide a summary of the current literature and guidance regarding identifying and adapting existing PROMs in clinical practice.
文摘近日,重庆医科大学感染性疾病分子生物学教育部重点实验室在国际肝脏病学领域顶级期刊HEPATOLOGY(影响因子:14.079)在线发表了题为"A functional variant in UBE2L3 contributes to HBV infection and maintains cccDNA stability by inducing degradation of APOBEC3A protein"研究成果。周莉副教授、任吉华博士和博士研究生程胜桃为本篇文章的第一作者,陈娟研究员和黄爱龙教授为共同通讯作者。这是数月来,该杂志又一次发表课题组相关研究工作。
基金the Youth Medical Talent of Jiangsu Province,No.QNRC2016475。
文摘BACKGROUND Accurate assessment of the quality of academic journals is of great significance.While Journal Impact Factor(JIF),calculated by Clarivate and based upon the Web of Science literature database,and CiteScore(CS),developed by Elseiver and based upon the Scopus database,have enjoyed high uptake worldwide,efforts continue towards creation of other scientometric indexes that will provide evergreater qualitative insights into journal impact.Such efforts have yielded the newly-launched Journal Article Influence Index(JAII),which is based on the Reference Citation Analysis(RCA)database,an open multidisciplinary citation analysis database based on artificial intelligence technology.AIM To evaluate and summarize the similarities and differences between JAII and JIF/CS as journal evaluation indicators,and provide an intuitive method for visual representation of the related data.METHODS We searched the Journal Citation Reports to obtain the 2021 JIF list,downloaded the CS list updated in July on the Scopus website,and collected the comprehensive list of 2022 JAIIs from the RCA database(www.referencecitationanalysis.com).RESULTS Our research results revealed that by breaking through the time limit of mainstream journalevaluation methods, the JAII is able to perform well in data reliability, establishing its benefit as acomplementary scientometric index to JIF and CS.CONCLUSIONJAII provides comprehensive assessment of the quality and performance of journals.
基金the Key Research and Development Program of Hunan Province,No.2020SK3022.
文摘BACKGROUND Although coronavirus disease 2019(COVID-19)presents primarily as a lower respiratory tract infection,increasing data suggests multiorgan,including the gastrointestinal(GI)tract and liver,involvement in patients who are infected by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).AIM To provide a comprehensive overview of COVID-19 in gastroenterology and hepatology.METHODS Relevant studies on COVID-19 related to the study aim were undertaken through a literature search to synthesize the extracted data.RESULTS We found that digestive symptoms and liver injury are not uncommon in patients with COVID-19 and varies in different individuals.The most common GI symptoms reported are diarrhea,nausea,vomiting,and abdominal discomfort.Other atypical GI symptoms,such as loss of smell and taste and GI bleeding,have also been reported along with the evolvement of COVID-19.Liver chemistry abnormalities mainly include elevation of aspartate transferase,alanine transferase,and total bilirubin.It is postulated to be related to the binding of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)virus to the angiotensin converting enzyme-2 receptor located on several different human cells.CONCLUSION Standardized criteria should be established for diagnosis and grading of the severity of GI symptoms in COVID-19 patients.Gastroenterology and hepatology in special populations,such as children and elderly,should be the focus of further research.Future long-term data regarding GI symptoms should not be overlooked.
