Artificial Intelligence is evolving in every discipline of education; medicine is no exception. Physicians and patients are getting aware of the need to be knowledgeable and engaged with AI in order to embrace it judiciously. There is growing mandate for AI to be integrated into medical school curriculum. The western countries have moved quickly to integrate AI into medicine, but India has been slow to embrace this vital wave of the future, likely due to lack of access to AI data. In light of this gap, the current study seeks to explore how Indian medical and nursing students view AI in medicine, gauge their interest in structured AI training during their undergraduate studies, and explore their understanding of the ethical implications surrounding AI. Methodology: 105 Medical and 72 nursing students of a rural college in Karnataka were involved in the survey to assess their knowledge of AI and its applications in medical education and healthcare, after informed consent and ethical clearance. This survey evaluated 6 key aspects of AI in medicine. Students submitted answer forms online in the classroom. Crosstab Chi-square analyses done. Results: 177 participants completed the survey. Over 90% expressed favorable opinions toward AI in healthcare and its support for medical students. Compared to nursing students, medical students were less likely to feel knowledgeable about AI, or see it as a threat. However, they were more aware of AI’s influence on patients. Conclusion: Medical and nursing students view AI optimistically and support its integration into healthcare curricula.

Keywords: Artificial intelligence; Deep learning algorithms; Healthcare profession; Medical education; Artificial intelligence in medicine

Corresponding Author: Uma SV, Email: uma.sv@smsimsr.org

Introduction

Artificial Intelligence (AI) is quickly reshaping the world of modern healthcare. With its ability of analyzing through massive amounts of data in just seconds, AI is speeding up diagnoses, assessing risks, predicting treatment outcomes, and managing complications more effectively. AI tools are already helping patients better understand their symptoms and encouraging them to seek medical help, which ultimately boosts their quality of life.1 Impressively, AI has shown it can perform on par with, or even outshine, human experts in areas like cancer treatment recommendations.2 Its growing presence includes uses in robotic-assisted surgeries, virtual nursing assistants, and advanced medical image analysis, making it an essential resource for both patients and healthcare providers.3

AI, which is defined as “the science and engineering of making intelligent machines,” involves tasks like decision-making, speech and image recognition, and language translation.3,4 The rapid rise of AIpowered applications, such as ChatGPT, with subscription of 100 million users in just two months, showcases the global excitement for AI and its potential to transform various fields.5 In medical education, AI presents opportunities to enhance learning through personalized education, datadriven insights, and simulation-based training. By tailoring AI education to match students’ preferred learning styles like self-directed learning, small group discussions, or visual and auditory methods— can improve its effectiveness.6

Given this rising influence, global organizations are realizing the importance of preparing healthcare professionals to collaborate with AI. The World Medical Association has urged the inclusion of AIrelated topics in medical training, stressing the need for awareness of both its possibilities and limitations.7 Similarly, in 2019, the Standing Committee of European Doctors commended that AI training be integrated throughout all levels of medical education—undergraduate, residency, and continuing education—highlighting the necessity of equipping future doctors with the knowledge and skills to use AI responsibly.8

While AI has captured significant attention for its wide-ranging applications—from diagnostics and treatment planning to clinical research, administrative tasks, and drug development— medical education has yet to fully embrace it.4-6 Around the world, countries are adopting AI to improve healthcare delivery, with clinicians increasingly turning to tools like machine learning, neural networks, and deep learning in their diagnostic and therapeutic practices.9-12 However, the integration of AI into undergraduate medical education remains patchy, likely due to a lack of solid data to guide its design and implementation.13

To create effective AI training programs, it’s crucial to grasp how medical and nursing students view AI, including their awareness, readiness, and ethical concerns. However, research in this area, especially within the Indian context, is still quite limited. Grunhut et al. (2021) pointed out the need for national surveys to gauge medical students’ attitudes toward AI, which could guide curriculum development and pinpoint the realistic expectations and skills future physicians will require.7 Unfortunately, many existing studies fall short of providing the comprehensive assessment that’s essential for this purpose.3 Despite the acknowledged advantages, the incorporation of AI education into medical curricula remains uneven. To tackle this issue, it’s essential to have a solid understanding of current student perspectives.

In light of this gap, the current study seeks to explore how Indian medical and nursing students view AI in medicine, gauge their interest in structured AI training during their undergraduate studies, and explore their understanding of the ethical implications surrounding AI. As the future users of AI tools in clinical settings, the attitudes and expectations of health care trainees are vital for successfully weaving AI into healthcare delivery and medical education.

Materials and Methods

The 105 Medical (first and second year) and 72 nursing students (first, second and third year) of rural medical college in Karnataka were involved in the survey to assess their knowledge of AI and its applications in medical education and healthcare, after informed consent and Ethical clearance. This survey evaluated 6 key aspects of AI in medicine, including its role in medical training and practice of medicine, as well as concerns surrounding its utilization. The questionnaire has 25 questions under the six sections of AI (Table 1).4 point Likert scale was used with Strongly agree/ agree /disagree/ strongly disagree. For the analysis of results agree and strongly agree were clubbed together as one and disagree/ strongly disagree into another group. The questionnaire was developed and tested through a pilot study. The questionnaire was sent by email and the students submitted their answer forms online in the classroom. Crosstab Chi-square analyses were conducted to assess the association between the outcomes and professions.

Results

A total of 177 participants completed the survey, with 52.5% (n=85) identifying as female and remaining males (n=92). Overall, participants expressed favorable opinions towards the utility of AI in healthcare (>90%). More than 90% of participants agree or strongly agree that AI will be a powerful ally to medical students. Compared with nursing students, medical students were less likely to consider themselves knowledgeable about various AI application in medicine (p=0.0219), believe AI will play a major role in medical training (p=0.0428), be concerned about student misuse of AI (p=0.0028), think that AI can replace physician (p=0.0003) or AI is a threat to practice medicine (p=0.0056). However, Medical students are more likely to be aware that AI is influencing patients (p=0.0192). The results are tabulated in

Table 1: Results of the questionnaire

Table 1: Results of the Questionnaire

Discussion:

The findings suggest that both the medical and nursing students have positive attitude towards AI but there is subtle differences in concerns and overall outlook on AI role in health care and medical education

Medical students seems more knowledgeable regarding the technological aspects of AI(83.7%) compared to nursing students (77.9 %) whereas nursing students have greater awareness of AI in daily life as well in creative applications as arts and science suggesting extracurricular exposure differences. Both the groups perceive AI as a supportive tool in medical education as a powerful ally and to reduce learning burden. These indicate that they have high expectations for AI to help in personalized learning and for access of information. Nursing students (89.7%)strongly believed that AI will play a role in medical education more than the medical students (77.7%). Nursing students feared that AI would replace physicians, which reflects their anxiety about job security. Almost all the students perceived AI as a collaborative tool rather than a threat and majority also believed that AI will revolutionize health care hence it compels a need for integration of AI in curriculum and requirement of regulatory guidelines and ethical oversight.

Blease et al.1 (2019), conducted semi structured interview with 18 general practitioners of UK and explored that they believe in AI assisting in diagnosis and as in our study they too were concerned about the ethical issues and job security. They were anticipating for a collaborative work between AI and GPs. Tipol emphasizes the AI should be used not to substitute human intelligence but in freeing up doctors time for compassionate care, shared decision making, and building trust which are the need for the hour in healthcare.3

Similar to our study, an online survey,7,8 conducted by Grunhut et al. (2021),revealed the strong demand among 2,170 medical students from multiple countries of six continents, for formal education,14 in AI for future physicians to be competent and ethically grounded in using AI tools in healthcare. The curricular reforms incorporating generative AI in medical education to be classified as “learning about AI,” “learning with AI,” and “learning aside from AI. 15

The CPME guidelines,8 also emphasizes that AI should enhance medical practice without compromising patient safety and autonomy. A meta-analysis analyzed 82 studies that evaluated performance of Deep learning (DL) algorithms with healthcare professional in interpreting medical images and concluded the diagnostic performance of DL models were comparable or higher to that of healthcare professionals.12,16 Incorporating the AI curriculum in medical training will ensure the future clinicians would be equipped with skills to enhance healthcare delivery system and patient outcome through AI.17-19

Conclusions:

This study illustrates that medical and nursing students have quite an optimistic view toward the impact of artificial intelligence in health and medical education. It demonstrated their awareness of AI technologies to increase the efficacy of learning; assist in clinical practice; and transform the medical profession. However, concerns regarding ethical issues, privacy, excessive use of technology, and institutional readiness were on the rise, especially with nursing students. Medical students seemed more confident and less worried about AI replacing physicians, while nursing students were more worried about job security. The findings confirm that an urgent need exists to incorporate structured AI education into healthcare curricula so that future professionals will not only able to practically apply these technologies but well also able to navigate the ethical, legal, and practical implications regarding AI in clinical practice.

Supplementary Materials: Table 1: Results of the questionnaire

Author Contribution: Conceptualization, Dr. Sathish Babu, Dr. Chaya Prasad.; Methodology: Dr. Sathish Babu, Dr. Uma SV, Dr. Chaya Prasad ,Dr. Rama P Sai, Dr. Fanglong; Formal Analysis: Dr. Chaya Prasad ,Dr.Rama P Sai, Dr. Fanglong; Writing - Original Draft Preparation, Dr. Sathish Babu, Dr. Uma SV; 5. Writing - Review & Editing, Dr. Sathish Babu, Dr. Uma SV, Dr. Chaya Prasad, Dr. Rama P Sai, Fanglong

Funding: This research received no external funding

Institutional Review Board Statement: The reported study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of SMSIMSR.

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Acknowledgments: We sincerely acknowledge all the students who participated in the study, all the faculty who helped in the study and the Statistician

Conflicts of Interest: The authors declare no conflicts of interest.

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