Abstract
Background
The rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students’ perceptions regarding the credibility and effectiveness of AI as a learning tool and to explore the dynamics of integrating AI in medical education.
Methodology
A cross-sectional study was carried out across medical colleges in Pakistan. A 26-question survey was developed using Google Forms from previously validated studies. The survey assessed demographics of participants, basic understanding of AI, AI as a learning tool in medical education and socio-ethical impacts of the use of AI. The data was analyzed using SPSS (v 26.0) to derive descriptive and inferential statistics.
Result
A total of 702 medical students aged 18 to 26 years (mean age 20.50 ± 1.6 years) participated in the study. The findings revealed a generally favorable attitude towards AI among medical students (80.3%), with the majority considering it an effective (60.8%) and credible (58.4%) learning tool in medical education. Students agreed that AI learning optimized their study time (60.3%) and provided up-to-date medical information (63.1%). Notably, 65.7% of students found AI more efficient in helping them grasp medical concepts compared to traditional tools like books and lectures, while 66.8% reported receiving more accurate answers to their medical inquiries through AI. The study highlighted that medical students view traditional tools as becoming increasingly outdated (59%), emphasizing the importance of integrating AI into medical education and creating dedicated AI tools (80%) for the medical education.
Conclusion
This study demonstrated that AI is an effective and credible tool in medical education, offering personalized learning experiences and improved educational outcomes. AI tools are helping students learn medical concepts by cutting down on study-time, providing accurate answers, and ultimately improving study outcomes. We recommend developing dedicated AI tools for medical education and their formal integration into medical curricula, along with appropriate regulatory oversight to ensure AI can enhance human abilities rather than acting as a replacement for humans.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12909-025-06704-y.
Keywords: Artificial intelligence, Deep learning, Educational technology: healthcare, Medical education, Machine learning
Introduction
AI is defined as “the science and engineering of making intelligent machines” [1]. It involves developing computer systems that can perform tasks requiring human intelligence e.g. speech recognition, visual perception, decision-making, and language translation [2]. The emergence of AI has been ground breaking in all frontiers; whether it’s automating processes, improving decision-making, analyzing market trends, or optimizing investment strategies. ChatGPT reached a record breaking 100 million users in just two months, solidifying its position as the fastest-growing consumer application ever. This unprecedented milestone underscores the transformative power of AI [3]. Due to its potential, AI sparked significant interest across the globe.
Incorporation of AI in medical education has the potential to revolutionize learning methods, improve educational outcomes, and ultimately contribute to better patient care. To improve medical education, it is essential to recognize the preferred learning styles of medical students. A recent study in Pakistan revealed that the majority of the students prefer self-learning, with other favored methods and styles including small group discussions, traditional class lectures, aural, visual, and reading/writing. Identifying these preferences helps tailor educational approaches to better meet the needs of medical students [4]. Despite the growing interest in emerging technologies, medical education has not kept in pace with the significant advancements in artificial intelligence. Although there have been multiple calls for action, the integration of AI training into undergraduate medical education remains limited, likely due to a lack of research-based evidence [5]. As AI continues to expand in healthcare, incorporating AI education in undergraduate medical education will be highly beneficial for future medical practice, reaching trainees early in their careers. The approach to teaching through AI in undergraduate medical education curricula should be done according to the best available evidence. Given AI’s relative novelty in medical education, a comprehensive literature review is necessary to identify existing evidence, highlight any gaps and conducting further research [6].
Artificial intelligence presents a transformative opportunity as a learning tool in medical education, offering personalized, adaptive learning experiences that can significantly enhance student outcomes [7, 8]. This personalization is especially valuable given the diverse learning preferences among medical students. Integrating AI into medical education also addresses a critical issue: time constraints. Medical students often face overwhelming schedules with limited time to engage deeply with multiple resources. AI tools can streamline learning by efficiently curating relevant content, automating assessments, and providing instant feedback, thus saving valuable time and allowing students to focus more on understanding and applying complex medical concepts. By optimizing study time and improving resource management, AI can significantly alleviate the burden on medical students, making learning more efficient and effective [9]. AI tools not only contribute to theoretical education but can also a play role in development of specific skills related to medical curriculum. A 2024 study highlighted the use of new AI tools that have aided medical students in learning of clinical and surgical skills. These AI tools evaluate students in real-time and provide feedback for improvement. Students have utilized these tools for assistance in minimally invasive surgery, tumor resection, suturing and catheterization. AI tools were also able to effectively evaluate skills of students and discriminate them into groups such as proficient and novice. The study concluded that AI tools can be instrumental to medical education through the avenues of student evaluation, teacher evaluation, and providing feedback to students and teachers [10].
The application of AI is not limited to medical education but has broader use in the field of medicine. The medical community has been captivated by AI due to its capabilities in aiding disease diagnosis, tumor detection, drug discovery and providing personalized treatment plans. AI is becoming increasingly vital across various aspects of medicine, including radiology, neurosurgery, dermatology, Alzheimer’s disease, breast cancer and pharmacology [11, 12]. Deep learning has empowered AI to analyze extensive datasets and provide precise responses. Integration of deep learning for medical image analysis in computer-aided diagnosis has supported clinicians in decision making and enhanced the precision and effectiveness of different diagnostic and treatment procedures [13]. In this context, AI has served as a second opinion for medical professionals. This is merely the tip of the iceberg; AI’s potential encourages exploration of new paths and continued innovation.
In recent years, there has been a surge in research exploring the perceptions and attitudes of medical students and professionals towards AI, as well as its inclusion as a subject in medical curriculum. The rationale for investigating the role of AI as teaching tool in medical education is that, despite the vast amount of literature, very limited studies have focused on this aspect of AI in medicine. Now that medical students are increasingly turning towards AI to study the medical curriculum, it is crucial that the credibility of the information provided by AI and the true effectiveness of these tools be determined through evidence-based research. The education of the new generation of healthcare professionals requires careful oversight, as it has a profound impact on patient health outcomes.
This research seeks input from medical students on AI’s effectiveness in reducing study time and delivering medical information efficiently. Ensuring the credibility of AI-generated information is crucial for patient care in this critical field. It also aims to assess students’ perspectives on the reliability of such information.
Methods
A multi-institute cross-sectional study was carried out in Pakistan from May 2024 to October 2024. An online survey created with Google Forms (Google, LLC) was used to collect data for the study. A 26 questions long questionnaire was designed for the study from previously validated studies [1, 14–18], which is attached as supplementary file. The questions in each section were collected using a 5-point Likert scale. On average, the participants took 5 min to finish the survey.
The subsections of survey were as follows:
General Information.
Knowledge of Artificial Intelligence.
Effectiveness of Artificial Intelligence.
Credibility of Artificial Intelligence.
The subsection “General Information” consisted of six questions aimed at collecting demographic data. The categories included age, gender, name of the medical institute, province of the medical institute, year of undergraduate study, and discipline e.g., Bachelor of Medicine and Bachelor of Surgery (MBBS) and Bachelor of Dental Surgery (BDS). The “Knowledge of Artificial Intelligence” subsection included six questions, exploring the participants’ general understanding of technology and AI, its application in daily life, and its potential to transform the field of medicine. The “Effectiveness of Artificial Intelligence” subsection contained seven questions that assessed how AI tools contribute to optimizing study methods, saving time, and delivering relevant content to enhance student performance. Lastly, the “Credibility of Artificial Intelligence” subsection, comprising six questions, evaluated the reliability and medical accuracy of information provided by AI in comparison to traditional study resources.
A Pilot Study was conducted in April, 2024 with 16 participants to check for discrepancies, usability, and functionality of the questionnaire. The initial survey consisted of 24 questions, two additional questions were included to better assess the effectiveness and credibility of AI as an educational tool. Other minor changes were made to improve the language, clarity, and uniformity of the questionnaire. Cronbach’s alpha values for each section were calculated to assess the internal consistency of the final questionnaire. The values ranged from 0.68 to 0.85 (Knowledge of AI = 0.68, Effectiveness of AI = 0.85, and Credibility of AI = 0.84). High Alpha values suggest that the survey tool was internally consistent. Statistical Analysis was performed using SPSS v27.0 and Microsoft Excel. We derived descriptive and inferential statistics. The descriptive analysis is presented as frequency tables and charts, shown in Figs. 1, 2, 3 and 4; Table 1. For inferential analysis we employed independent t-test to test various hypotheses and assess the difference between the attitudes and perceptions of various groups, shown in Tables 2 and 3. For the independent t-test a p-value of < 0.05 was considered significant.
Fig. 1.
Regional distribution of study participants
Fig. 2.
Which of the following AI tool do you use most frequently?
Fig. 3.
Effectiveness of artificial intelligence
Fig. 4.
Credibility of artificial intelligence
Table 1.
Demographic data
| Demographic | Number (n) | Percentage | |
|---|---|---|---|
| Age | |||
| 18–20 | 394 | 56.1% | |
| 20–25 | 300 | 42.7% | |
| Over 25 | 8 | 1.13% | |
| Discipline | |||
| MBBS | 595 | 84.8% | |
| BDS | 107 | 15.3% | |
| Institute | |||
| CIMS, Multan | 294 | 41.9% | |
| IIMC | 154 | 21.9% | |
| NSHS | 60 | 8.50% | |
| AKU | 29 | 4.10% | |
| NMU | 28 | 4.00% | |
| Ayub Medical College | 15 | 2.10% | |
| HITEC-IMS | 14 | 2.00% | |
| SKZMDC | 11 | 1.56% |
Abbreviations MBBS: Bachelor of medicine and Bachelor of Surgery, BDS: Bachelor of Dental Surgery, CIMS: CMH Institute of Medical Sciences, IIMC: Islamic International Medical College, NSHS: Nust School of Health Sciences, AKU: Agha Khan University, NMU: Nishtar Medical University, HITEC-IMS: HITEC Institute of Medical Sciences. SKZMDC: Shaikh Khalifa Bin Zayed Al-Nahyan Medical and Dental College
Table 2.
General perception of artificial intelligence
| Perception of tech-savvy vs. non-tech-savvy individuals | P-value |
|---|---|
|
Q 12. Tech savvy people had a more positive attitude towards AI and its ability to revolutionize medicine |
0.000 |
|
Q 13. Tech savvy and non-tech savvy participants were equally fearful of AI taking up jobs of Health professionals |
0.064 |
Table 3.
Effectiveness of artificial intelligence
| Attitudes towards effectiveness of AI | P-value |
|---|---|
|
Q14. Tech-savvy participants were more likely to prepare test compared to non-tech-savvy |
0.000 |
|
Q19. AI provides more precise answers to my queries related to my curriculum compared to conventional study resources. |
0.000 |
|
Q20. Tech-savvy and non-tech-savvy expressed equal concern regrading AI potentially replacing conventional study resources. |
0.000 |
Ethical approval
was obtained from the Ethics Review Committee of NUST School of Health Sciences (NSHS), National University of Sciences and Technology, Islamabad, Pakistan. All procedures adhered to the ethical standards set by the institutional committee. The first page of the questionnaire contained a consent form that all participants were required to complete to proceed further. Respondents were informed about the nature and purpose of the survey before providing consent, and they were given the option to withdraw at any time. The participants were informed that their responses would remain anonymous. Additionally, confidentiality of the participants was ensured by design, with no collection of identifiable personal information, such as names or email addresses. The data was only available to the investigators. The sample size of our study was calculated by an online sample size calculator. We included a range of public and private medical schools across Pakistan, to ensure diverse representation of the healthcare system. Students enrolled in disciplines other than medicine (MBBS and BDS) were excluded from the research, as were those studying medicine outside Pakistan. We employed convenience sampling to collect responses. The questionnaire was distributed by the researchers through faculty members and medical students across various medical schools. Our study focused on medical students as they represent the future of medicine. The education and training of future health professionals is crucial, as it has a direct influence on patient care and the health care system. Furthermore, exploring their perceptions helps identify challenges and opportunities for implementing AI in medical education while offering unique insights to the global dialogue on AI.
Results
Demographic data
Seven hundred and two medical students (n = 702) from across Pakistan responded to the survey. The age distribution of the participants was between 18 and 26. A total of 338 male and 364 female students participated in the study. Demographic data including age and discipline of study is shown in Table 1. In Pakistan, the MBBS and BDS degree programs are of five years. In our study, students from all the five years of medical and dental training participated. A total of 702 students participated, out of which 264 were from first year, 188 were from second year, 159 were from third year, 62 were from fourth year and 29 were from final year of studies. Furthermore, students from 22 medical colleges across Pakistan took part in the study, with a significant number of responses from CIMS Multan (41.9%), followed by IIMC (21.9%) and NSHS (8.5%) among other medical colleges. Table 1 represents number of responses from various medical colleges in detail.
Students from different provinces and capital territory of Pakistan participated in the study, details are shown in Fig. 1.
General perception of artificial intelligence
A significant majority, 84.7% of the participants, were aware of the ongoing conversation regarding AI and its application in the field of medicine. The level of awareness of AI did not significantly differ between males and females ( 85.5% vs. 84.1%). A p value of 0.310 suggests that there was no statistically significant difference between attitudes of female and male towards AI. Majority of the participants (75.5%), strongly agreed or agreed that they were technologically adept (tech savvy), while only 8% (n = 56) disagreed. The medical students used a variety of AI tools to study the concepts of medical curriculum, details of different AI tools used by medical students is shown in Fig. 2.
A significant number (74.2%) of the participants agreed that AI had assisted them in completing day-to-day tasks. There was a notable disparity in attitudes towards AI between tech-savvy and non-tech-savvy participants, with those who were tech-savvy generally having a more positive outlook. A p-value of 0.000 of suggest that there was a statistically significant difference between the attitudes of tech-savvy vs. non-tech-savvy participants. Nearly 90.8% of Tech savvy participants believed AI could revolutionize medicine compared to 58.7% of non tech savvy participants. The results from independent t-test, highlighting the disparity in attitudes between tech-savvy and non-tech-savvy participants, are presented in Table 2.
There was a positive attitude towards AI, with 80.3% agreeing that AI could improve healthcare. However, there was also fear among medical students that AI could lead to the replacement of human medical professionals (44.8% agreed compared to 36.8% respondents that disagreed). This fear resonated with both tech savvy and non-tech savvy participants. The p value suggests that there was no statistically significant difference between attitudes of tech savvy and non-tech savvy participants, both groups being concerned about job security. Details are shown in Table 2.
Effectiveness of artificial intelligence
A majority (59.3%) reported using AI tools very often or often to prepare for medical school test and exams. Tech-savvy participants were more likely to use AI tools to prepare for their medical school tests and exams compared to non-tech-savvy participants, and a statistically significant difference was noted between the attitudes of both groups as detailed in Table 3. Furthermore, 80% of the participants reported using AI at least once a week or more frequently to study concepts of medical curriculum. A small number (12.1%) reported using AI tools once a month while 8% of the participants said that they have never used AI to study concepts of medical curriculum. Most respondents (60.6%) agreed that AI tools have enabled them to reduce study time and learn medical concepts more quickly (65.7%) compared to traditional study resources e.g. books and lectures. Student’s opinions on effectiveness of AI in improving grades and reducing study time are detailed in Fig. 3. Furthermore, the respondents also believed that AI offered more precise answers to their medical queries (66.8%). A similar trend was seen here as well, tech-savvy participants believed that AI tools provided more accurate information than conventional study tools compared to non-tech-savvy participants and a statistically significant difference was seen between both groups as shown in Table 3.
The effectiveness of AI is apparent, with 59% of respondents believing that traditional study tools will become outdated. However, this also reinforces students’ concerns about AI potentially replacing jobs held by medical professionals.
Credibility of artificial intelligence
The research also revealed that medical students considered information sourced from AI to be medically accurate (58.2%) as illustrated in Fig. 4. Furthermore, tech-savvy participants believed AI tools provide medically accurate information compared to non-tech-savvy participants, as detailed in Table 4. Another significant finding was that majority of participants agreed that AI tools were even more credible than conventional tools e.g. books and lectures. While more participants (53.3%) agreed that AI provided more clinically relevant information than conventional tools, 23.6% participants expressed disagreement with this view. Participants (64.2%) also revealed that AI enabled them to understand concepts of topics that were previously challenging for them. Participants (64.2%) also revealed that AI enabled them to understand concepts of topics that were previously challenging for them. Details about the difference in attitudes between tech-savvy and non-tech-savvy participants are provided in Table 4. Most participants said that AI provided more up to date information (63%) for their medical study compared to traditional study tools. Figure 4 shows details of students’ perceptions about the credibility of AI tools.
Table 4.
Credibility of artificial intelligence
| Attitudes towards credibility of AI | P-value |
|---|---|
|
Q21. Tech-savvy participants believed AI provides medically accurate information compared to non-tech-savvy. |
0.000 |
|
Q23. Tech-savvy and non-tech-savvy participants believed that AI was effective in helping them understand concepts that they had previously struggled to grasp using traditional study tools |
0.000 |
|
Q25. Tech-savvy participants believed AI provides more up to date information compared to conventional study tools |
0.000 |
A significant majority (83%) believe that a dedicated AI tool is essential for medical education. This belief was even stronger among tech-savvy participants (87.5%), advocating for the creation of a new tool, compared to non-tech-savvy participants (62.5%), (P value = 0.000). Table 4 highlights the difference in views of tech-savvy and non-tech-savvy participants concerning the credibility of AI.
Discussion
Implementation of AI as a learning tool in medical education has the potential to improve healthcare and clinical practices by increasing efficiency and offering credible medical information. Most literature regarding AI revolves around its knowledge, perception, and attitudes towards AI. While, some other studies assess the potential for integrating AI as a subject in medical education.
This study evaluated the demographics of medical students across Pakistan, providing insights into the age, gender distribution, academic discipline, and institutional representation among participants. With a total of 702 responses, the data reflects a substantial participation from various medical institutions, highlighting the relevance of AI as a learning tool. The age distribution of the participants was between 18 and 26, with the mean age of the participants being 20.50 ± 1.6. These demographic insights are critical when considering the integration of AI tools in medical education. The youthfulness of the participants suggests a potential openness to adopting innovative learning methods, while the gender balance may foster diverse insights into how AI can be tailored to meet the learning preferences of all students. Furthermore, focusing on MBBS and BDS students underscores the importance of developing AI tools that specifically address the complexities and demands of medical training.
Integration of AI tools, including platforms like ChatGPT, is increasingly relevant in medical education and practice. In the context of Pakistan, this study sought to evaluate the perceptions of medical and dental students regarding AI as a learning tool. As of our results mentions that most commonly used AI tools by our study participants includes ChatGpt (64%), MetaAI (24.5%), Google Gemini (9%) whereas (3%) don’t use any of the above tools.
A Canadian cross-sectional study assessed the attitude and perception of AI among medical students. An over whelming majority (94%) agreed that AI’s applications in medicine would become more wide spread in the future and would improve medicine (84%). Majority of the participants also agreed that AI would be cost effective, optimize physician’s work and benefit patients. 67% of the participants were in favor of formally teaching AI in medical curriculum [14]. Cross-sectional researches across Syria [15], Sultan Qaboos University, Oman [19], Nigeria [20] and Catalonia [21] all showed similar trends; positive attitudes towards AI.
The researches above give compelling evidence of both medical students and professionals embracing AI and the importance of integrating AI in various aspects of medicine. The findings from this study highlight a promising outlook on the acceptance of AI tools like ChatGPT among medical students in Pakistan, aligning with trends observed in other countries. The shared positive perceptions across different populations suggest a growing recognition of AI’s potential to enhance medical education and practice. As we move forward, integrating AI into the medical curriculum can be pivotal in preparing future healthcare providers for a technology-driven landscape.
Our research took a different approach by investigating the potential and practicality of incorporating AI into medical education as a tool for learning; an aspect that prior studies had not explored. The study demonstrated AI’s effectiveness by reducing study time (60.6%), providing precise answers to medical queries (66.8%), and aiding students in increasing their grades during medical school (60.8%). Furthermore, credibility of AI was also evident as 58.2% participants agreed that AI provides medical accurate information and more up to date information compared to conventional study methods (63%). The statistics above prove that integration of AI as a learning tool will optimize medical education and allow improved results. This aligns with the findings from a Kuwaiti study, where 92.4% of participants agreed that integrating AI into medical education would facilitate the learning process & 82.1% of participants believed all medical students should be educated about AI [22].
A 2021 research in Pakistan, showed that 71.28% (n = 335) of its participants, mainly medical professionals and students, had general knowledge of AI. Positive attitude of participants can be seen in the study as 66.6% participants agreed that integration of AI in disease diagnosis will help eradicate errors. A majority also agreed that AI could be utilized for pathological diagnostic techniques, in radiology, managing of Covid-19 pandemic and be integrated in medical curriculum [23]. A systemic review of articles up to 2023 of attitudes, knowledge, and perceptions of dentists and dental students toward artificial intelligence also showed a similar pattern. Majority of the participants were knowledge able about AI and agreed over its potential to revolutionize dentistry [24]. Our research data showed that the knowledge (84.7%) and education of AI had increased in Pakistan since the previous studies. The students also held a more positive attitude towards AI and its application in medicine (80.3%).
Now more than ever, incorporation of AI into medical education is becoming increasingly essential, considering that a significant number of students are already utilizing AI to learn medical concepts and prepare for exams. The integration of AI in medical education can be achieved by creation of a dedicated AI tool. In our study, 83% of participants expressed support for the creation of a dedicated AI tool for medical education. 63% of participants believed that AI tools provide up-to-date information, while 37% disagreed. Additionally, 58% of participants felt that AI tools deliver medically accurate information, whereas 41.7% disagreed. A 2023 by Alkhaaldi et al.., on medical students’ experiences and perceptions of ChatGPT and AI found that the majority (62.3%) acknowledged that the responses generated by ChatGPT needed to be verified and also that AI has the potential to make more accurate diagnoses than physicians. These insights highlight the need for a specialized AI tool in the medical education [21]. Our study’s findings, consistent with the existing literature, show that the medical community is open to embracing AI-driven advancements. AI tools hold the potential to make medical education more effective, alleviating the stress and burden of work usually faced by the students. Additionally, innovative AI tools allow students to improve their clinical and surgical skills. AI-based tools provide instant personalised feedback and enable students to improve on an individual level. AI tools can enable more rigorous assessment of the student’s performance, and offer deeper insights to faculty and the students about individual strengths and weaknesses. AI-powered feedback systems can help uncover hidden trends and identify gaps in knowledge, allowing curriculum makers to refine and adapt medical curriculum. AI is transforming the medical education from a broad, generalised format to a more precise and individualised approach. AI can elevate the standard and practice of medical education.
On one hand, there’s a positive attitude towards AI, likely due to its potential to revolutionize healthcare (80.3%) through innovations like diagnostic assistance and personalized treatment plans. On the other hand, there’s also a fear among medical students that these rapid advancements could lead to the replacement of human medical professionals in the foreseeable future. Integration of AI in medical curriculum will also address another significant concern held by medical students; tech savvy and non tech savvy both held the view that AI will replace medical professionals (44.8%) and conventional study tool (59%) in the foreseeable future. The loss of jobs is a cause of significant distress in medical community. A 2024 study evaluating perception of Indian medical students about AI showed a similar results with 37.6% believing that AI can replace medical professionals and 69.2% feared that there will be a decrease in humanistic aspect of medicine [25]. A study conducted in December 2022 revealed concerns about the ethical implications of AI. The participants, comprising 168 students, expressed that 63.4% believed AI could diminish the humanistic aspects of medicine. Additionally, 40% of the students agreed that AI might lead to fewer job opportunities for physicians in the future [21]. Another 2021 Chinese study among health professionals in ophthalmology reported that 66% respondents believed that AI tools could partly replace ophthalmologists in the future [26]. This fearful trend has been seen across the medical community, from medical students to medical professionals. While advancements in AI continue to reshape the field of medicine, human-to-human interaction remains a fundamental aspect of the art of medicine. A balance between AI and human aspect of medicine needs to be established to ensure that the core values of empathy and communication are maintained in healthcare and the roles of human in medicine can be preserved.
Regulation of AI in medicine by developing policies is important for addressing ethical concerns and safeguarding human jobs in healthcare. Government and medical institutes need to develop clear guidelines to ensure that AI systems prioritize patient welfare, maintaining ethical standards in decision-making processes such as diagnosis and treatment [17]. By enforcing regulations, we can prevent biases, errors, and misuse of sensitive medical data, promoting trust between patients, healthcare providers, and AI technologies. Moreover, regulatory oversight can eradicate fears of job loss among healthcare professionals by emphasizing AI’s role as a tool to enhace human abilities instead of replacing them. At this juncture, role of government and medical institutes is pivotal. AI will inevitably impact the medical education of students and have a profound impact on healthcare system. Therefore, it is responsibility of institutes and leaders in medicine to pick up the mantle and lead the path for integration of AI in medical curriculum formally. Development and regulation of new AI tools will ensure that medical students consume medially accurate information while gaining all the benefits that come with AI. Through responsible regulation, the integration of AI in medicine can enhance patient care, uphold ethical principles, and sustain the integrity of healthcare professions in an evolving technological landscape. Exposure, learning and use of AI by medical students and professionals will improve health care, alleviate fear regarding AI and enable smooth integration of AI in the field of medicine.
Limitations
Our study had some limitations. Firstly, there may have been demographic imbalances. A large number of the responses were from Punjab province, this can be counterbalanced by the fact that Punjab accounts for 53% of Pakistan’s total population and has the highest number of medical schools. Furthermore, we faced data collection constraints due to internet connectivity and limited access in certain underdeveloped regions of Pakistan. Our study relied on self-reported data that can potentially introduce bias. To combat biases such as social desirability bias, we kept the responses anonymous and participants were made aware of this, reducing the risk of bias. The anonymous nature of our survey helped address privacy and trust concerns that some medical students might have had, which could otherwise limit the study. Additionally, Sect. 2 ‘Knowledge of AI’ had a Cronbach’s alpha of 0.68. Although the value for this section was lower than that of the other sections of the questionnaire, the value is still considered acceptable, and the overall consistency of the questionnaire was high.
Conclusion
The majority of medical and dental students in Pakistan are actively using AI tools to study, with ChatGPT being the most used AI tool for medical education. AI tools are enhancing students’ ability to grasp medical concepts more quickly and efficiently, while also providing credible, up-to-date information. On the other hand, a notable difference was seen between the attitudes of tech-savvy and non-tech-savvy individuals, with non-tech-savvy participants being more fearful of AI. In future, development of dedicated AI tools and their formal integration into medical education by medical institutes is important to supplement traditional resources, and preparing students for a digital healthcare landscape.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We would like to express our sincere gratitude to Munir Ahmad Bosan and Hasnat Tanveer for their invaluable contributions to this research. Their efforts in data collection were essential to the success of this study.
Abbreviations
- AI
Artifical Intellegence
- MBBS
Bachelor of medicine and Bachelor of Surgery
- BDS
Bachelor of Dental Surgery
- CIMS
CMH Institute of Medical Sciences
- IIMC
Islamic International Medical College
- NSHS
Nust School of Health Sciences
- AKU
Agha Khan University
- NMU
Nishtar Medical University
- HITEC-IMS
HITEC Institute of Medical Sciences
- SKZMDC
Shaikh Khalifa Bin Zayed Al-Nahyan Medical and Dental College
Author contributions
Study Design: A.S.; D.U.O.; K.M.; Y.W. Data Analysis: A.S.; F.T.; K.S.; N.K.; M.A.J.; D.U.O.; K.M.; Y.W.Manuscript Writing: A.S.; F.T.; K.S.; D.U.O.; K.M.; Y.W. Manuscript Editing: D.U.O.; K.M.; Y.W. Supervision: Y.W. Final Approval: A.S.; F.T.; K.S.; N.K.; M.A.J.; D.U.O.; K.M.; Y.W.
Funding
This work is not support by any funding.
Data availability
Additional data can be provided on suitable request to corresponding author.
Human ethics and consent to participate
Ethical approval was obtained from the Ethics Review Committee of NUST School of Health Sciences (NSHS), National University of Sciences and Technology, Islamabad, Pakistan. The first page of the questionnaire contained a consent form that all participants were required to complete to proceed further. Respondents were informed about the nature and purpose of the survey before providing consent, and they were given the option to withdraw at any time.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Khalid Muhammad, Email: k.muhammad@uaeu.ac.ae.
Yasir Waheed, Email: yasir.waheed@nshs.nust.edu.pk.
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Additional data can be provided on suitable request to corresponding author.