Artificial intelligence education in the faculty of medicine in Indonesia

By Jum’atil Fajar*

(Source: Getty Images)

One of the sub-programmes in the Artificial Intelligence (AI) Programme Roadmap for Health Priority Areas 2020-2045 listed in the Indonesian National Artificial Intelligence Strategy is the 4P Paradigm Basic Training (Preventive, Prediction, Participatory, Personalized) for medical workers covering big data, AI, internet of things (IoT) and genetics. The institutions expected to carry out this activity are the Ministry of Health, the National Research and Innovation Agency, the Ministry of Communication and Information, the Healthtech Association, the Indonesian Doctors Association, and other related professional associations working in collaboration. The programme is expected to run from 2021 to 2023.

To be able to train medical faculty on issues related to AI we need to consider key aspects such as content, accessibility of training, the supply of potential lecturers and the reach and coverage of the training provided.

To find out how students learn about AI, I reached out to Professor Ari Fahrial Syam, Dean of the Faculty of Medicine, University of Indonesia (FKUI). Professor Syam explained that the Indonesian Medical Education and Research Institute (IMERI) under FKUI has a medical technology cluster. This cluster collaborates with various departments in FKUI to develop AI. Students are also involved in the process. IMERI offers a series of e-courses on topics related to AI. One of these courses is AI Applications in the World of Health and Medicine, which is available in Indonesian.

The availability of courses in Indonesian is important because language is often a barrier for students. In reality, there are many courses on AI in Healthcare in English, including: The Complete Healthcare Artificial Intelligence Course 2021 available on Udemy, AI in Healthcare – AI For Patient Engagement by KeyReply, AI in Healthcare specialization courses offered on Coursera, Artificial Intelligence in Healthcare by Stanford Online and Artificial Intelligence in Health Care by MIT Sloan School of Management and the MIT J-Clinic. However, all these courses have fees, which can be another obstacle for medical personnel to access training.

While content is one important piece of the puzzle, we also need to consider the supply of lecturers if education to medical students is to increase. To assess the potential availability of lectures, I analysed the data available at the IMERI website, including the number of ongoing research projects related to AI in medicine and digital health. There are currently 18 studies. The topics studied are quite diverse, including tuberculosis, pneumonia, tumour regrowth, plastic surgery, mental disorders, cervical cancer, diabetes, the elderly, auscultation of lung sounds and stroke. If we look at the list of names of the researchers, they already represent the sections of radiology, sports medicine, internal medicine, plastic surgery, ear nose throat and neck, and nerves. Although they do not represent all sections of the medical faculty, it is hoped that these doctors could become pioneers in the development of AI education in the medical world in Indonesia.

While there is significant progress being made now, there are concerns in Indonesia about the centralisation of the expertise in its capital, Jakarta, leaving other regions behind.

Training medical personnel on AI represents an enormous challenge, not only for Indonesia but for countries around the world. While medical faculties in big cities have begun to involve students in the development of AI, we need to ensure that the process remains equitable across regions, ensuring educational institutions located in remote areas also get a seat at the table.


*Jum’atil Fajar is an AI enthusiast. He holds a Masters degree in Health Sciences. He helped develop the hospital management information system. He currently manages the Hospital Accreditation Data Management Information System.