Are Indian Medical Students Prepared For The Inevitable Artificial Intelligence?

Dear Editor, Artificial intelligence (AI), once a jargon of the tech world, has already started encroaching on the medical f ield. Artificial intelligence aims at incorporating problem-solving and decision-making capabilities, intelligence and discernment of the human mind into machines, especially computers.¹ The AI systems have varying levels of autonomy which analyses the data and inputs given to it and gives decisions, recommendations, or predictions for the given objectives. For a country like India with a population of 1.3 billion, adopting AI in healthcare is mandatory not only to handle the enormous amount of data but also make quality services available to all with the existing resources.²

The scope of AI in healthcare is humongous. It includes virtual health assistance, taking patient history, automated referral, triaging, automated imaging studies, robotic surgery, identification of redundant health tasks, managing medical records, reduction of medication errors, remote monitoring of patients, identification of fraud in insurance etc. Artificial intelligence can also be used in the accurate cancer diagnosis, targeted diagnosis and treatment of diseases like tuberculosis, screening of diabetic retinopathy and coronavirus disease 2019 (COVID-19) cases, diagnosis of rare diseases, and accurate diagnosis of dermatological lesions.³

 At present, AI usage in India is being adopted to automate time-consuming and large volume repetitive tasks. There is advancement in utilizing AI for precision  diagnostics. Apollo Hospitals which is a leading private healthcare chain in India has launched a clinical decision support tool called Clinical Intelligence Engine (CIE), which uses AI and machine learning. The system is used to assimilate clinical data from Apollo Hospitals’ knowledge base and real-world clinical data, which would enable early detection of diseases and making faster decisions.⁴ In the next 5 years, India will progress from AI adopters to co-innovators in developing novel AI systems for therapeutics.⁵

The concept of AI roots long back, it is still struggling to flourish in the Indian healthcare sector. In India, a student who opts for mainstream subjects like biology in high school is admitted to medical schools. Since computer science and mathematics are not their mainstream subjects, they find it difficult to understand the logic and principles applied in AI.⁶ Additionally, there is no formal training or bridge courses for medical students in AI in medical schools. This is a crucial issue of concern because today’s medical students become tomorrow’s clinicians. It is high time that medical curriculum designers should evaluate and bring forth ideas to incorporate AI training for medical students. It is essential that medical students in India be trained in basic AI learning. We should update the medical curriculum to include logical, reasoning, and analytical learning methods to cope with the rapidly ameliorating trend in AI. Only if the fundamentals of AI training are incorporated in the first and second year, the students will be able to apply that to clinical scenarios when  they move to the third and final year. The unification of computer science with medical subjects will enable the understanding of AI principles much better. Students must be encouraged to take up research related to AI, which will facilitate them in becoming more competent in handling AI in the future.^7,8

Implementing AI in medical education has its own obstacles, such as the lack of digitization in medical colleges and hospitals, financial constraints, etc. Hence, data acquisition, which forms the basis of AI algorithms, is hampered. Furthermore, AI implementation in healthcare is a multidisciplinary approach because it requires data analysts who can handle large amounts of data, health professionals who can ensure clinical relevance and accuracy, educators in computer science, etc. This multidisciplinary approach is currently lacking in medical schools in India.⁷

The current scenario is that the medical students in India has to be trained on basic AI learning. It is necessary that we update our curriculum so as to include more of logical, reasoning, analytical learning methods to cope with the rapidly ameliorating trend in AI. Only if the fundamentals of AI training is incorporated in first and second year, the students will be able to apply that to clinical scenarios when they move to third and final year. Unification of computer science with medical subjects will enable understanding of AI principles much better. Students must be encouraged to take up research works related to AI which will facilitate them to become more competent in handling AI in future.

To conclude, undoubtedly AI has the potential to make significant changes in healthcare like reducing human errors, decreasing medical costs and labor, rapid processing of data, and making fast, accurate diagnosis. But to achieve this, the medical fraternity should be trained and equipped with the AI knowledge. The medical curriculum should be reformed and must integrate AI into medical education. This will equip the emerging generation of medical professionals to face the inevitable integration of AI in the future.