Background:The rapid integration of generative artificial intelligence(genAI)into medical education offers significant opportunities for personalized learning,efficiency,and access.However,its implementation also rais...Background:The rapid integration of generative artificial intelligence(genAI)into medical education offers significant opportunities for personalized learning,efficiency,and access.However,its implementation also raises complex ethical concerns that,if unaddressed,may compromise academic integrity,professional identity,and learner equity.This review aimed to identify the primary ethical risks associated with genAI use in medical education and propose solid measures to mitigate these issues.Methods:A structured narrative review was conducted in accordance with the Scale for the Assessment of Narrative Review Articles(SANRA).A focused literature search was performed across PubMed/MEDLINE and Google Scholar for peer-reviewed,English-language articles published from January 2023 to May 2025.Studies were included if they addressed ethical issues in the use of genAI in undergraduate or postgraduate medical education.Data were extracted into related themes,and findings were synthesized into risk and mitigation categories.Results:A total of 27 records were included.Eight principal categories of ethical risks associated with genAI in medical education emerged:(1)academic integrity erosion,(2)cognitive deskilling,(3)algorithmic bias and opacity,(4)privacy and surveillance concerns,(5)moral and humanistic diminishment,(6)faculty role displacement,(7)commercialization and inequity,and(8)legal-regulatory ambiguity.Each risk was matched with targeted mitigation strategies proposed in the literature,including institutional genAI governance frameworks,genAI literacy training,reinforcement of humanistic pedagogy,establishment of ethical oversight bodies,curricular integration of ethical reflexivity,equity-centered implementation policies,faculty development for genAI integration,and transparent data governance protocols.Conclusion:Generative AI presents both transformative promise and substantial ethical risks in medical education.Proactive,ethically grounded integration-guided by institutional oversight,curriculum reform,and equity safeguards-is essential to realize its benefits while protecting the integrity and humanity of medical training.展开更多
Diabetes mellitus is a major cause of visual deficiency among working age adults and is estimated for visual impairment in 4.8%of the 37 million individuals who are visually impaired all over the world(1,2).A wide ran...Diabetes mellitus is a major cause of visual deficiency among working age adults and is estimated for visual impairment in 4.8%of the 37 million individuals who are visually impaired all over the world(1,2).A wide range of diabetic retinopathy microvascular changes are seen in the retina.Throughout the years,a screening device utilizing both advanced non-mydriatic fundus imaging and traditional mydriatic fundus camera has been utilized and has been found to be useful(1).展开更多
<strong>Background: </strong>Disseminated Intravascular Coagulation (DIC) is a life threatening complication frequently observed in acute leukemia. Among the morphological varieties of Acute Myeloid Leukae...<strong>Background: </strong>Disseminated Intravascular Coagulation (DIC) is a life threatening complication frequently observed in acute leukemia. Among the morphological varieties of Acute Myeloid Leukaemia (AML), Acute Promyelocytic Leukaemia (APL) is well established to cause DIC. But there have been reports noted that abnormal DIC parameters also commonly observed in the patients with non-APL AML. This study evaluated the DIC parameters & DIC score according to International Society of Thrombosis and Haemostasis (ISTH) in newly diagnosed non-APL AML patients. <strong>Materials and Methods:</strong> This cross-sectional observational study was conducted in the Department of Haematology, B中央人民政府, Dhaka, Bangladesh. 48 newly diagnosed non-APL AML patients were enrolled. Platelets count was measured by auto analyzer (Sysmax XT 2000i/Pentra ABX-120DX) as well as checked manually. Prothrombin time, fibrinogen, D-Dimer were measured using STAGO Coagulation analyzer. The ISTH-DIC scoring system was used to calculate DIC score. The statistical analysis was carried out using the Statistical Package for Social Sciences version 24.0 for Windows. Chi-Square test & Fisher exact test was used for categorical variables. Unpaired t-test was used to compare mean between groups. For all statistical tests, p-value less than 0.05 was considered as statistically significant. <strong>Results: </strong>By analyzing 48 newly diagnosed patients with non-APL AML, found that DIC developed in 14.6% patients at presentation. Among the DIC parameters, PT and D-dimer were significantly higher in patients presented with DIC. Patients with DIC exhibit lower expression of CD117, CD34, HLA-DR and statistically significant association with negative expression of HLA-DR (p-value 0.034). No significant association was found between presence of DIC and age, gender, bleeding at presentation, morphological type, WBC count or peripheral blast percentage.<strong> Conclusion:</strong> Abnormalities of DIC parameters in common in patients with AML. A significant portion of patients with DIC have no apparent symptom or bleeding. So, routine screening of DIC parameter at presentation is recommended for early diagnosis & effective management of DIC.展开更多
文摘Background:The rapid integration of generative artificial intelligence(genAI)into medical education offers significant opportunities for personalized learning,efficiency,and access.However,its implementation also raises complex ethical concerns that,if unaddressed,may compromise academic integrity,professional identity,and learner equity.This review aimed to identify the primary ethical risks associated with genAI use in medical education and propose solid measures to mitigate these issues.Methods:A structured narrative review was conducted in accordance with the Scale for the Assessment of Narrative Review Articles(SANRA).A focused literature search was performed across PubMed/MEDLINE and Google Scholar for peer-reviewed,English-language articles published from January 2023 to May 2025.Studies were included if they addressed ethical issues in the use of genAI in undergraduate or postgraduate medical education.Data were extracted into related themes,and findings were synthesized into risk and mitigation categories.Results:A total of 27 records were included.Eight principal categories of ethical risks associated with genAI in medical education emerged:(1)academic integrity erosion,(2)cognitive deskilling,(3)algorithmic bias and opacity,(4)privacy and surveillance concerns,(5)moral and humanistic diminishment,(6)faculty role displacement,(7)commercialization and inequity,and(8)legal-regulatory ambiguity.Each risk was matched with targeted mitigation strategies proposed in the literature,including institutional genAI governance frameworks,genAI literacy training,reinforcement of humanistic pedagogy,establishment of ethical oversight bodies,curricular integration of ethical reflexivity,equity-centered implementation policies,faculty development for genAI integration,and transparent data governance protocols.Conclusion:Generative AI presents both transformative promise and substantial ethical risks in medical education.Proactive,ethically grounded integration-guided by institutional oversight,curriculum reform,and equity safeguards-is essential to realize its benefits while protecting the integrity and humanity of medical training.
文摘Diabetes mellitus is a major cause of visual deficiency among working age adults and is estimated for visual impairment in 4.8%of the 37 million individuals who are visually impaired all over the world(1,2).A wide range of diabetic retinopathy microvascular changes are seen in the retina.Throughout the years,a screening device utilizing both advanced non-mydriatic fundus imaging and traditional mydriatic fundus camera has been utilized and has been found to be useful(1).
文摘<strong>Background: </strong>Disseminated Intravascular Coagulation (DIC) is a life threatening complication frequently observed in acute leukemia. Among the morphological varieties of Acute Myeloid Leukaemia (AML), Acute Promyelocytic Leukaemia (APL) is well established to cause DIC. But there have been reports noted that abnormal DIC parameters also commonly observed in the patients with non-APL AML. This study evaluated the DIC parameters & DIC score according to International Society of Thrombosis and Haemostasis (ISTH) in newly diagnosed non-APL AML patients. <strong>Materials and Methods:</strong> This cross-sectional observational study was conducted in the Department of Haematology, B中央人民政府, Dhaka, Bangladesh. 48 newly diagnosed non-APL AML patients were enrolled. Platelets count was measured by auto analyzer (Sysmax XT 2000i/Pentra ABX-120DX) as well as checked manually. Prothrombin time, fibrinogen, D-Dimer were measured using STAGO Coagulation analyzer. The ISTH-DIC scoring system was used to calculate DIC score. The statistical analysis was carried out using the Statistical Package for Social Sciences version 24.0 for Windows. Chi-Square test & Fisher exact test was used for categorical variables. Unpaired t-test was used to compare mean between groups. For all statistical tests, p-value less than 0.05 was considered as statistically significant. <strong>Results: </strong>By analyzing 48 newly diagnosed patients with non-APL AML, found that DIC developed in 14.6% patients at presentation. Among the DIC parameters, PT and D-dimer were significantly higher in patients presented with DIC. Patients with DIC exhibit lower expression of CD117, CD34, HLA-DR and statistically significant association with negative expression of HLA-DR (p-value 0.034). No significant association was found between presence of DIC and age, gender, bleeding at presentation, morphological type, WBC count or peripheral blast percentage.<strong> Conclusion:</strong> Abnormalities of DIC parameters in common in patients with AML. A significant portion of patients with DIC have no apparent symptom or bleeding. So, routine screening of DIC parameter at presentation is recommended for early diagnosis & effective management of DIC.
