Objective:To analyze the application value of artificial intelligence(AI)in the comprehensive service pathway for rational clinical use of western medicines.Methods:A sample of 73 patients undergoing western medicine ...Objective:To analyze the application value of artificial intelligence(AI)in the comprehensive service pathway for rational clinical use of western medicines.Methods:A sample of 73 patients undergoing western medicine treatment from December 2024 to March 2025 was selected and divided into groups by lottery.Group A received AI-assisted management for rational clinical use of western medicines,while Group B received conventional management.Thirty-six patients taking oral western medicines were included in Group B.Results:Group A outperformed Group B in terms of the irrationality rate of western medicine usage,drug management scores,adverse reaction rates,complaint rates,and satisfaction levels,with p<0.05.Conclusion:AI-assisted rational clinical use of western medicines enhances drug management quality,reduces the irrationality rate of medication usage,and decreases complaint rates related to western medicine usage.展开更多
Histopathological analysis of chronic wounds is crucial for clinicians to accurately assess wound healing progress and detect potential malignancy.However,traditional pathological tissue sections require specific stai...Histopathological analysis of chronic wounds is crucial for clinicians to accurately assess wound healing progress and detect potential malignancy.However,traditional pathological tissue sections require specific staining procedures involving carcinogenic chemicals.This study proposes an interdisciplinary approach merging materials science,medicine,and artificial intelligence(AI)to develop a virtual staining technique and intelligent evaluation model based on deep learning for chronic wound tissue pathology.This innovation aims to enhance clinical diagnosis and treatment by offering personalized AI-driven therapeutic strategies.By establishing a mouse model of chronic wounds and using a series of hydrogel wound dressings,tissue pathology sections were periodically collected for manual staining and healing assessment.We focused on leveraging the pix2pix image translation framework within deep learning networks.Through CNN models implemented in Python using PyTorch,our study involves learning and feature extraction for region segmentation of pathological slides.Comparative analysis between virtual staining and manual staining results,along with healing diagnosis conclusions,aims to optimize AI models.Ultimately,this approach integrates new metrics such as image recognition,quantitative analysis,and digital diagnostics to formulate an intelligent wound assessment model,facilitating smart monitoring and personalized treatment of wounds.In blind evaluation by pathologists,minimal disparities were found between virtual and conventional histologically stained images of murine wound tissue.The evaluation used pathologists’average scores on real stained images as a benchmark.The scores for virtual stained images were 71.1%for cellular features,75.4%for tissue structures,and 77.8%for overall assessment.Metrics such as PSNR(20.265)and SSIM(0.634)demonstrated our algorithms’superior performance over existing networks.Eight pathological features such as epidermis,hair follicles,and granulation tissue can be accurately identified,and the images were found to be more faithful to the actual tissue feature distribution when compared to manually annotated data.展开更多
Dental caries,a chronic disease characterized by tooth decay,occupies the second position in terms of disease burden and is primarily caused by cariogenic bacteria,especially Streptococcus mutans,because of its acidog...Dental caries,a chronic disease characterized by tooth decay,occupies the second position in terms of disease burden and is primarily caused by cariogenic bacteria,especially Streptococcus mutans,because of its acidogenic,aciduric,and biofilm-forming capabilities.Developing novel targeted anti-virulence agents is always a focal point in caries control to overcome the limitations of conventional anti-virulence agents.The current study represents an up-to-date review of in silico approaches of drug design against dental caries,which have emerged more and more powerful complementary to biochemical attempts.Firstly,we categorize the in silico approaches into computer-aided drug design(CADD)and AI-assisted drug design(AIDD)and highlight the specific methods and models they contain respectively.Subsequently,we detail the design of anti-virulence drugs targeting single or multiple cariogenic virulence targets of S.mutans,such as glucosyltransferases(Gtfs),antigen I/II(AgI/II),sortase A(SrtA),the VicRK signal transduction system and superoxide dismutases(SODs).Finally,we outline the current opportunities and challenges encountered in this field to aid future endeavors and applications of CADD and AIDD in anti-virulence drug design.展开更多
Applying artificial intelligence(AI)technology to language teaching has become a new trend in higher education.As an AI tool fully leveraging deep learning technology,Deepseek has been increasingly adopted in universi...Applying artificial intelligence(AI)technology to language teaching has become a new trend in higher education.As an AI tool fully leveraging deep learning technology,Deepseek has been increasingly adopted in university English teaching.This paper analyzes Deepseek’s practical applications in university English teaching,including automated interactive learning,quality assessment,specialized learning modules as well as integration of ideological and political education in English teaching.Additionally,it discusses major challenges encountered during Deepseek’s application,such as insufficient student interaction and concerns related to data privacy and information security.Finally,the paper explores future directions for Deepseek in university English education,proposing strategies to promote human-AI collaborative teaching models and enhance data integration to improve model output quality.展开更多
With the continuous advancement of the New Engineering Education initiative,universities are raising the standards for cultivating engineering talents.C Programming Language,as a core course for computer science and r...With the continuous advancement of the New Engineering Education initiative,universities are raising the standards for cultivating engineering talents.C Programming Language,as a core course for computer science and related majors,plays a fundamental role in developing logical thinking,programming skills,and engineering practice.However,problems such as outdated content,weak practical connections,and single assessment methods still exist in current teaching,which affects both learning outcomes and students’skill development.Based on the outcome-based education(OBE)approach and supported by AI-assisted teaching tools,this paper proposes a reform plan focusing on teaching content,instructional methods,and evaluation systems.The goal is to enhance students’overall abilities and practical innovation skills,and to align the course more closely with modern industry needs.展开更多
The rapid integration of artificial intelligence(AI)into software development,driven by large language models(LLMs),is reshaping the role of programmers from traditional coders into strategic collaborators within Indu...The rapid integration of artificial intelligence(AI)into software development,driven by large language models(LLMs),is reshaping the role of programmers from traditional coders into strategic collaborators within Industry 4.0 ecosystems.This qualitative study employs a hermeneutic phenomenological approach to explore the lived experiences of Information Technology(IT)professionals as they navigate a dynamic technological landscape marked by intelligent automation,shifting professional identities,and emerging ethical concerns.Findings indicate that developers are actively adapting to AI-augmented environments by engaging in continuous upskilling,prompt engineering,interdisciplinary collaboration,and heightened ethical awareness.However,participants also voiced growing concerns about the reliability and security of AI-generated code,noting that these tools can introduce hidden vulnerabilities and reduce critical engagement due to automation bias.Many described instances of flawed logic,insecure patterns,or syntactically correct but contextually inappropriate suggestions,underscoring the need for rigorous human oversight.Additionally,the study reveals anxieties around job displacement and the gradual erosion of fundamental coding skills,particularly in environments where AI tools dominate routine development tasks.These findings highlight an urgent need for educational reforms,industry standards,and organizational policies that prioritize both technical robustness and the preservation of human expertise.As AI becomes increasingly embedded in software engineering workflows,this research offers timely insights into how developers and organizations can responsibly integrate intelligent systems to promote accountability,resilience,and innovation across the software development lifecycle.展开更多
The rapid development of artificial intelligence(AI)has brought significant changes to academic writing,raising important questions about authorship,originality,and how writing is taught and learned.While AI-based wri...The rapid development of artificial intelligence(AI)has brought significant changes to academic writing,raising important questions about authorship,originality,and how writing is taught and learned.While AI-based writing tools are now widely available,academic writing instruction has not kept pace and continues to rely on conventional pedagogical approaches.This paper introduces a conceptual framework called the Academic Writing and AI Integration(AWAI)Framework,which seeks to address this gap in a structured and pedagogically informed manner.Grounded in interdisciplinary scholarship,the AWAI Framework emphasizes the integration of three key elements:scholarly content knowledge,academic writing conventions,and AI literacy.Rather than reporting empirical findings,this study presents a theoretical model aimed at supporting educators and students as they navigate the opportunities and challenges posed by AI in academic contexts.The framework outlines a balanced approach to incorporating AI tools into writing instruction,while upholding the standards of academic rigor and ethical responsibility.Through this work,academic writing is reconsidered in light of emerging technological influences.The framework contributes to broader discussions about educational innovation and provides a foundation for future inquiry into the evolving relationship between human authors and intelligent systems in scholarly communication.展开更多
This research takes AI-assisted teaching design as the starting point to explore new paths for classroom teaching reform.The study constructs a four-step practical framework of“conceptual update-intelligent support-t...This research takes AI-assisted teaching design as the starting point to explore new paths for classroom teaching reform.The study constructs a four-step practical framework of“conceptual update-intelligent support-teaching reconfiguration-reflection and improvement”,guiding teachers to collaborate with AI in completing the diagnosis of learning situations,target positioning,activity design,and resource push,achieving the transformation from experience-driven to data-driven teaching paradigm.The practice shows that the intervention of AI not only expands the design vision of teachers but also gives rise to new classroom forms with diverse interactions and progressive layers,stimulating students’deep participation and personalized growth.The research proposes that the key to promoting deep collaboration between teachers and AI lies in enhancing the teaching interpretability of intelligent tools and creating a design culture of joint creation and continuous iteration,providing a feasible practical model for classroom transformation in the era of intelligence.展开更多
Purpose: This study examines the transformative impact of artificial intelligence (AI) in healthcare, focusing on its applications in medical diagnosis, drug discovery, surgery, and disease management while addressing...Purpose: This study examines the transformative impact of artificial intelligence (AI) in healthcare, focusing on its applications in medical diagnosis, drug discovery, surgery, and disease management while addressing ethical, technological, and social concerns. Method: A comprehensive literature review synthesizes research on AI applications, including AI-assisted diagnosis, drug discovery, robot-assisted surgery, stroke management, and artificial neurons. Findings: AI has enabled significant breakthroughs in healthcare, enhancing outcomes in diagnostics, personalized treatments, and surgical procedures. Despite its promise, challenges such as privacy, safety, and equitable access remain critical concerns. Research Limitations: The study relies on existing literature and lacks empirical validation of AI models, with its scope limited by the rapid evolution of AI technologies. Social Implications: The integration of AI raises concerns about privacy, patient rights, and equitable access, particularly in underserved regions, potentially exacerbating healthcare disparities. Practical Implications: The study urges healthcare practitioners to adopt AI tools for improved diagnostics and treatments while advocating for regulatory frameworks to ensure ethical and safe AI integration. Originality: This study offers a comprehensive review of AI’s transformative role in healthcare, emphasizing ethical considerations and providing actionable insights for researchers and practitioners.展开更多
Large language models,such as ChatGPT,use vast textual data to mimic human-like responses and interact with users in a natural conversational way.This capability has introduced several opportunities and challenges in ...Large language models,such as ChatGPT,use vast textual data to mimic human-like responses and interact with users in a natural conversational way.This capability has introduced several opportunities and challenges in the field of language education and has sparked both excitement and concern among language educators.This study seeks to contribute to the ongoing debate surrounding the advantages and drawbacks of using ChatGPT in the language classroom by attempting to evaluate its effectiveness in Arabic language learning,with a particular focus on teaching case endings.To achieve this,this study analyzes and discusses data collected from ChatGPT learning sessions,quizzes,and surveys conducted with university students studying Arabic.The findings of this study revealed that while ChatGPT was efficient in providing detailed and personalized explanations,it was deficient in providing accurate and reliable information regarding Arabic case endings.展开更多
The integration of Generative Artificial Intelligence(AIGC)into publishing institutions presents challenges such as conceptual ambiguity,technical barriers,and workforce anxiety regarding skill gaps.This study address...The integration of Generative Artificial Intelligence(AIGC)into publishing institutions presents challenges such as conceptual ambiguity,technical barriers,and workforce anxiety regarding skill gaps.This study addresses these issues by conducting an in-depth analysis of the current application status,challenges,and future development trends of AIGC in publishing,using the development of the Wenzheng Intelligent Publishing Platform as a case study.The paper proposes an agile,incremental strategy,starting with the implementation of AI-assisted manuscript review and proofreading systems.The effectiveness of this approach is validated through practical operational data.Ultimately,this research emphasizes that the publishing industry should actively embrace technological innovation while upholding its core values,thereby facilitating a gradual intelligent transformation through the comprehensive adoption of AI tools.展开更多
文摘Objective:To analyze the application value of artificial intelligence(AI)in the comprehensive service pathway for rational clinical use of western medicines.Methods:A sample of 73 patients undergoing western medicine treatment from December 2024 to March 2025 was selected and divided into groups by lottery.Group A received AI-assisted management for rational clinical use of western medicines,while Group B received conventional management.Thirty-six patients taking oral western medicines were included in Group B.Results:Group A outperformed Group B in terms of the irrationality rate of western medicine usage,drug management scores,adverse reaction rates,complaint rates,and satisfaction levels,with p<0.05.Conclusion:AI-assisted rational clinical use of western medicines enhances drug management quality,reduces the irrationality rate of medication usage,and decreases complaint rates related to western medicine usage.
基金supported by the Fundamental Research Funds for the Central Universities(No.20720230037)the National Natural Science Foundation of China(No.52273305)+2 种基金Natural Science Foundation of Fujian Province of China(No.2023J05012)State Key Laboratory of Vaccines for Infectious Diseases,Xiang An Biomedicine Laboratory(Nos.2023XAKJ0103071,2023XAKJ0102061)Natural Science Foundation of Xiamen,China(No.3502Z20227010).
文摘Histopathological analysis of chronic wounds is crucial for clinicians to accurately assess wound healing progress and detect potential malignancy.However,traditional pathological tissue sections require specific staining procedures involving carcinogenic chemicals.This study proposes an interdisciplinary approach merging materials science,medicine,and artificial intelligence(AI)to develop a virtual staining technique and intelligent evaluation model based on deep learning for chronic wound tissue pathology.This innovation aims to enhance clinical diagnosis and treatment by offering personalized AI-driven therapeutic strategies.By establishing a mouse model of chronic wounds and using a series of hydrogel wound dressings,tissue pathology sections were periodically collected for manual staining and healing assessment.We focused on leveraging the pix2pix image translation framework within deep learning networks.Through CNN models implemented in Python using PyTorch,our study involves learning and feature extraction for region segmentation of pathological slides.Comparative analysis between virtual staining and manual staining results,along with healing diagnosis conclusions,aims to optimize AI models.Ultimately,this approach integrates new metrics such as image recognition,quantitative analysis,and digital diagnostics to formulate an intelligent wound assessment model,facilitating smart monitoring and personalized treatment of wounds.In blind evaluation by pathologists,minimal disparities were found between virtual and conventional histologically stained images of murine wound tissue.The evaluation used pathologists’average scores on real stained images as a benchmark.The scores for virtual stained images were 71.1%for cellular features,75.4%for tissue structures,and 77.8%for overall assessment.Metrics such as PSNR(20.265)and SSIM(0.634)demonstrated our algorithms’superior performance over existing networks.Eight pathological features such as epidermis,hair follicles,and granulation tissue can be accurately identified,and the images were found to be more faithful to the actual tissue feature distribution when compared to manually annotated data.
基金supported by the Sichuan Science and Technology Program,China(Grant Nos.:2023ZYD0105 and 2023YFS0343)。
文摘Dental caries,a chronic disease characterized by tooth decay,occupies the second position in terms of disease burden and is primarily caused by cariogenic bacteria,especially Streptococcus mutans,because of its acidogenic,aciduric,and biofilm-forming capabilities.Developing novel targeted anti-virulence agents is always a focal point in caries control to overcome the limitations of conventional anti-virulence agents.The current study represents an up-to-date review of in silico approaches of drug design against dental caries,which have emerged more and more powerful complementary to biochemical attempts.Firstly,we categorize the in silico approaches into computer-aided drug design(CADD)and AI-assisted drug design(AIDD)and highlight the specific methods and models they contain respectively.Subsequently,we detail the design of anti-virulence drugs targeting single or multiple cariogenic virulence targets of S.mutans,such as glucosyltransferases(Gtfs),antigen I/II(AgI/II),sortase A(SrtA),the VicRK signal transduction system and superoxide dismutases(SODs).Finally,we outline the current opportunities and challenges encountered in this field to aid future endeavors and applications of CADD and AIDD in anti-virulence drug design.
文摘Applying artificial intelligence(AI)technology to language teaching has become a new trend in higher education.As an AI tool fully leveraging deep learning technology,Deepseek has been increasingly adopted in university English teaching.This paper analyzes Deepseek’s practical applications in university English teaching,including automated interactive learning,quality assessment,specialized learning modules as well as integration of ideological and political education in English teaching.Additionally,it discusses major challenges encountered during Deepseek’s application,such as insufficient student interaction and concerns related to data privacy and information security.Finally,the paper explores future directions for Deepseek in university English education,proposing strategies to promote human-AI collaborative teaching models and enhance data integration to improve model output quality.
基金funded by Xinjiang Natural Science Foundation of China(2023D01C52)University Key Project(2023YSZD004).
文摘With the continuous advancement of the New Engineering Education initiative,universities are raising the standards for cultivating engineering talents.C Programming Language,as a core course for computer science and related majors,plays a fundamental role in developing logical thinking,programming skills,and engineering practice.However,problems such as outdated content,weak practical connections,and single assessment methods still exist in current teaching,which affects both learning outcomes and students’skill development.Based on the outcome-based education(OBE)approach and supported by AI-assisted teaching tools,this paper proposes a reform plan focusing on teaching content,instructional methods,and evaluation systems.The goal is to enhance students’overall abilities and practical innovation skills,and to align the course more closely with modern industry needs.
文摘The rapid integration of artificial intelligence(AI)into software development,driven by large language models(LLMs),is reshaping the role of programmers from traditional coders into strategic collaborators within Industry 4.0 ecosystems.This qualitative study employs a hermeneutic phenomenological approach to explore the lived experiences of Information Technology(IT)professionals as they navigate a dynamic technological landscape marked by intelligent automation,shifting professional identities,and emerging ethical concerns.Findings indicate that developers are actively adapting to AI-augmented environments by engaging in continuous upskilling,prompt engineering,interdisciplinary collaboration,and heightened ethical awareness.However,participants also voiced growing concerns about the reliability and security of AI-generated code,noting that these tools can introduce hidden vulnerabilities and reduce critical engagement due to automation bias.Many described instances of flawed logic,insecure patterns,or syntactically correct but contextually inappropriate suggestions,underscoring the need for rigorous human oversight.Additionally,the study reveals anxieties around job displacement and the gradual erosion of fundamental coding skills,particularly in environments where AI tools dominate routine development tasks.These findings highlight an urgent need for educational reforms,industry standards,and organizational policies that prioritize both technical robustness and the preservation of human expertise.As AI becomes increasingly embedded in software engineering workflows,this research offers timely insights into how developers and organizations can responsibly integrate intelligent systems to promote accountability,resilience,and innovation across the software development lifecycle.
文摘The rapid development of artificial intelligence(AI)has brought significant changes to academic writing,raising important questions about authorship,originality,and how writing is taught and learned.While AI-based writing tools are now widely available,academic writing instruction has not kept pace and continues to rely on conventional pedagogical approaches.This paper introduces a conceptual framework called the Academic Writing and AI Integration(AWAI)Framework,which seeks to address this gap in a structured and pedagogically informed manner.Grounded in interdisciplinary scholarship,the AWAI Framework emphasizes the integration of three key elements:scholarly content knowledge,academic writing conventions,and AI literacy.Rather than reporting empirical findings,this study presents a theoretical model aimed at supporting educators and students as they navigate the opportunities and challenges posed by AI in academic contexts.The framework outlines a balanced approach to incorporating AI tools into writing instruction,while upholding the standards of academic rigor and ethical responsibility.Through this work,academic writing is reconsidered in light of emerging technological influences.The framework contributes to broader discussions about educational innovation and provides a foundation for future inquiry into the evolving relationship between human authors and intelligent systems in scholarly communication.
文摘This research takes AI-assisted teaching design as the starting point to explore new paths for classroom teaching reform.The study constructs a four-step practical framework of“conceptual update-intelligent support-teaching reconfiguration-reflection and improvement”,guiding teachers to collaborate with AI in completing the diagnosis of learning situations,target positioning,activity design,and resource push,achieving the transformation from experience-driven to data-driven teaching paradigm.The practice shows that the intervention of AI not only expands the design vision of teachers but also gives rise to new classroom forms with diverse interactions and progressive layers,stimulating students’deep participation and personalized growth.The research proposes that the key to promoting deep collaboration between teachers and AI lies in enhancing the teaching interpretability of intelligent tools and creating a design culture of joint creation and continuous iteration,providing a feasible practical model for classroom transformation in the era of intelligence.
文摘Purpose: This study examines the transformative impact of artificial intelligence (AI) in healthcare, focusing on its applications in medical diagnosis, drug discovery, surgery, and disease management while addressing ethical, technological, and social concerns. Method: A comprehensive literature review synthesizes research on AI applications, including AI-assisted diagnosis, drug discovery, robot-assisted surgery, stroke management, and artificial neurons. Findings: AI has enabled significant breakthroughs in healthcare, enhancing outcomes in diagnostics, personalized treatments, and surgical procedures. Despite its promise, challenges such as privacy, safety, and equitable access remain critical concerns. Research Limitations: The study relies on existing literature and lacks empirical validation of AI models, with its scope limited by the rapid evolution of AI technologies. Social Implications: The integration of AI raises concerns about privacy, patient rights, and equitable access, particularly in underserved regions, potentially exacerbating healthcare disparities. Practical Implications: The study urges healthcare practitioners to adopt AI tools for improved diagnostics and treatments while advocating for regulatory frameworks to ensure ethical and safe AI integration. Originality: This study offers a comprehensive review of AI’s transformative role in healthcare, emphasizing ethical considerations and providing actionable insights for researchers and practitioners.
基金This research received financial support from the College of Humanities and Sciences at Virginia Commonwealth University through the Seed Award program.
文摘Large language models,such as ChatGPT,use vast textual data to mimic human-like responses and interact with users in a natural conversational way.This capability has introduced several opportunities and challenges in the field of language education and has sparked both excitement and concern among language educators.This study seeks to contribute to the ongoing debate surrounding the advantages and drawbacks of using ChatGPT in the language classroom by attempting to evaluate its effectiveness in Arabic language learning,with a particular focus on teaching case endings.To achieve this,this study analyzes and discusses data collected from ChatGPT learning sessions,quizzes,and surveys conducted with university students studying Arabic.The findings of this study revealed that while ChatGPT was efficient in providing detailed and personalized explanations,it was deficient in providing accurate and reliable information regarding Arabic case endings.
文摘The integration of Generative Artificial Intelligence(AIGC)into publishing institutions presents challenges such as conceptual ambiguity,technical barriers,and workforce anxiety regarding skill gaps.This study addresses these issues by conducting an in-depth analysis of the current application status,challenges,and future development trends of AIGC in publishing,using the development of the Wenzheng Intelligent Publishing Platform as a case study.The paper proposes an agile,incremental strategy,starting with the implementation of AI-assisted manuscript review and proofreading systems.The effectiveness of this approach is validated through practical operational data.Ultimately,this research emphasizes that the publishing industry should actively embrace technological innovation while upholding its core values,thereby facilitating a gradual intelligent transformation through the comprehensive adoption of AI tools.
