Smita R Sorte, Alka T Rawekar, Sachin B Rathod, Nisha Surana Gandhi
{"title":"面向未来的医学:评估印度本科医学课程对人工智能教育的需求:对学生观点的混合方法调查。","authors":"Smita R Sorte, Alka T Rawekar, Sachin B Rathod, Nisha Surana Gandhi","doi":"10.4103/jehp.jehp_1030_24","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The medical community increasingly acknowledges the necessity for undergraduate medical curricula to formally incorporate Artificial Intelligence (A.I.) into the training of medical students to equip them with the essential skills. By the time Indian medical students complete their postgraduate training, which could span nearly a decade, A.I. tools will become more common place in clinical decision-making workflows. Despite the global trend towards emphasizing A.I. education in healthcare, Indian medical institutes lack mandates from higher authorities to incorporate A.I. into their curricula. Our study aims to assess the student's perspective regarding need for A.I. Education in Indian undergraduate medical curriculum (IUMC) and the educational needs of medical students, which may facilitate the development of a curriculum that prepares them for the challenges and opportunities presented by A.I. in medicine.</p><p><strong>Materials and methods: </strong>A cross sectional study was conducted at A.I.I.M.S, Nagpur. An exploratory survey was conducted on M.B.B.S. students from the 2019 batch to the 2023 batch using Google Forms. Data was analyzed using the Jamovi open statistical software solid version 2.3.28 (released 2024).</p><p><strong>Result: </strong>The survey was completed by 219 medical students. In total, 91.2% had no prior training in A.I. education, 87.1% of students hold positive views on incorporating A.I. education into the IMUC, and 80% believe that A.I. training should be experiential. No Gender difference was found between male and female students regarding perceived interest in A.I. education.</p><p><strong>Conclusion: </strong>The study highlights students' strong consensus on integrating A.I. into the IMUC, including hands-on practical applications, to enhance diagnostic skills. Medical schools should provide early exposure to A.I. Gender-neutral, experiential learning should be emphasized to meet the demands of current and future students.</p>","PeriodicalId":15581,"journal":{"name":"Journal of Education and Health Promotion","volume":"14 ","pages":"215"},"PeriodicalIF":1.4000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12200240/pdf/","citationCount":"0","resultStr":"{\"title\":\"Future-ready medicine: Assessing the need for A.I. education in Indian undergraduate medical curriculum: A mixed method survey of student perspectives.\",\"authors\":\"Smita R Sorte, Alka T Rawekar, Sachin B Rathod, Nisha Surana Gandhi\",\"doi\":\"10.4103/jehp.jehp_1030_24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The medical community increasingly acknowledges the necessity for undergraduate medical curricula to formally incorporate Artificial Intelligence (A.I.) into the training of medical students to equip them with the essential skills. By the time Indian medical students complete their postgraduate training, which could span nearly a decade, A.I. tools will become more common place in clinical decision-making workflows. Despite the global trend towards emphasizing A.I. education in healthcare, Indian medical institutes lack mandates from higher authorities to incorporate A.I. into their curricula. Our study aims to assess the student's perspective regarding need for A.I. Education in Indian undergraduate medical curriculum (IUMC) and the educational needs of medical students, which may facilitate the development of a curriculum that prepares them for the challenges and opportunities presented by A.I. in medicine.</p><p><strong>Materials and methods: </strong>A cross sectional study was conducted at A.I.I.M.S, Nagpur. An exploratory survey was conducted on M.B.B.S. students from the 2019 batch to the 2023 batch using Google Forms. Data was analyzed using the Jamovi open statistical software solid version 2.3.28 (released 2024).</p><p><strong>Result: </strong>The survey was completed by 219 medical students. In total, 91.2% had no prior training in A.I. education, 87.1% of students hold positive views on incorporating A.I. education into the IMUC, and 80% believe that A.I. training should be experiential. No Gender difference was found between male and female students regarding perceived interest in A.I. education.</p><p><strong>Conclusion: </strong>The study highlights students' strong consensus on integrating A.I. into the IMUC, including hands-on practical applications, to enhance diagnostic skills. Medical schools should provide early exposure to A.I. Gender-neutral, experiential learning should be emphasized to meet the demands of current and future students.</p>\",\"PeriodicalId\":15581,\"journal\":{\"name\":\"Journal of Education and Health Promotion\",\"volume\":\"14 \",\"pages\":\"215\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2025-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12200240/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Education and Health Promotion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4103/jehp.jehp_1030_24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Education and Health Promotion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/jehp.jehp_1030_24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
Future-ready medicine: Assessing the need for A.I. education in Indian undergraduate medical curriculum: A mixed method survey of student perspectives.
Background: The medical community increasingly acknowledges the necessity for undergraduate medical curricula to formally incorporate Artificial Intelligence (A.I.) into the training of medical students to equip them with the essential skills. By the time Indian medical students complete their postgraduate training, which could span nearly a decade, A.I. tools will become more common place in clinical decision-making workflows. Despite the global trend towards emphasizing A.I. education in healthcare, Indian medical institutes lack mandates from higher authorities to incorporate A.I. into their curricula. Our study aims to assess the student's perspective regarding need for A.I. Education in Indian undergraduate medical curriculum (IUMC) and the educational needs of medical students, which may facilitate the development of a curriculum that prepares them for the challenges and opportunities presented by A.I. in medicine.
Materials and methods: A cross sectional study was conducted at A.I.I.M.S, Nagpur. An exploratory survey was conducted on M.B.B.S. students from the 2019 batch to the 2023 batch using Google Forms. Data was analyzed using the Jamovi open statistical software solid version 2.3.28 (released 2024).
Result: The survey was completed by 219 medical students. In total, 91.2% had no prior training in A.I. education, 87.1% of students hold positive views on incorporating A.I. education into the IMUC, and 80% believe that A.I. training should be experiential. No Gender difference was found between male and female students regarding perceived interest in A.I. education.
Conclusion: The study highlights students' strong consensus on integrating A.I. into the IMUC, including hands-on practical applications, to enhance diagnostic skills. Medical schools should provide early exposure to A.I. Gender-neutral, experiential learning should be emphasized to meet the demands of current and future students.