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Table of Contents
Year : 2022  |  Volume : 19  |  Issue : 2  |  Page : 73-74

Training tomorrow's global digital health leaders

1 Department of Medicine and Bioengineering, Stanford University, Stanford, USA
2 Department of Psychiatry and Medicine, Duke University, Durham, Carolina, USA

Date of Submission22-Feb-2022
Date of Decision03-Mar-2022
Date of Acceptance04-Mar-2022
Date of Web Publication15-Apr-2022

Correspondence Address:
P Murali Doraiswamy
Departments of Psychiatry and Medicine, Duke University, Durham, Carolina
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/am.am_32_22

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How to cite this article:
Kaushal A, Doraiswamy P M. Training tomorrow's global digital health leaders. Apollo Med 2022;19:73-4

How to cite this URL:
Kaushal A, Doraiswamy P M. Training tomorrow's global digital health leaders. Apollo Med [serial online] 2022 [cited 2022 Jul 1];19:73-4. Available from: https://www.apollomedicine.org/text.asp?2022/19/2/73/343318

A novel virus was identified and sequenced in days. Precision vaccines are designed in record time. Advanced models are predicting infections, hospitalizations, and deaths guiding public health interventions around the world. Patients are monitored in their homes using advanced AI-embedded sensors and communication devices. Each of these biomedical innovations was made possible by advances in an altogether different discipline: computer science and engineering.[1],[2] The rapid rise of the interplay of biomedical and quantitative sciences has created a demand for individuals with a background in both. India, with a rich tradition of producing world-class physicians, scientists, and engineers, may be well positioned to train tomorrow's digital health innovators.

There are several reasons for the rapid rise of the role of artificial intelligence [AI] and computational sciences in biomedicine. The steady exponential decrease in the cost of computing power, digital storage, and communication bandwidth has enabled the creation of entirely new types of devices, as we see in the mobile phones, cameras, and other sensors now ever present in our daily lives. Perhaps, more surprising is the speed with which high-performance algorithms and approaches to make use of the wealth of computational power and digital data have emerged. Disciplines such as simulation, modeling, and machine learning have flourished in recent years. The combination of powerful and affordable hardware, powerful and affordable software and algorithms, and ubiquitous connected computing is leading to a reexamination of the entire biomedical enterprise, from drug development to patient care.[1],[2] And given that many of the enabling technologies of today barely existed just 15 years ago, it is possible that the most exciting tools are yet to come.

However, developing technical solutions to problems in biomedicine is not as easy as point-and-click. Each discipline has different languages, concepts, intuitions, and cultures, which can take years of experience to internalize.[2] The consequences of failure are high, especially when it comes to any technology affecting patient care. And solving a technological problem is often just a starting point not the finish line. Successful adoption of that innovation requires a careful understanding of how it fits into the workflows of biomedicine, whether in a hospital or a medical research enterprise. Even choosing the right problems to tackle in the first place, before assembling teams of doctors and engineers, requires thought and consideration.

Given these complexities, there is an increasing need for people trained in both the computational and biomedical domains.[2] Globally, we observe emerging opportunities for individuals at all stages of their careers. Individuals in the middle or later stages of their careers, often with deep expertise in one domain, can pursue training in an interdisciplinary program (for example, a cardiologist obtaining a Master's degree in Biomedical Informatics). In the US, several medical colleges offer joint degrees that can simultaneously train students in both medicine and computer science fields. And engineering colleges are beginning to offer undergraduate degrees in biomedical computation to train students in the language, culture, and techniques of both fields at a time when their professional intuitions are still forming. One of us (AK) helped launch Stanford School of Engineering's undergraduate major in Biomedical Computation (bmc.stanford.edu), which has graduated over 100 students since inception.[2]

Opportunities for India

India's deep expertise in training world-class doctors and engineers positions the country as a key contributor to the biomedical innovation of today and tomorrow. Over the past 5 years, India has jumped 35 spots in the Global Innovation Index and holds the #1 rank in the information communication services export sector.[3] India-trained computer scientists today serve as founders or CEOs of some of Silicon Valley's largest and most innovative companies. India is the fourth largest producer of AI papers (behind US, UK, and China) and in the top 10 for AI patents[4] – this may be an underestimate since many AI papers/patents from the US also are by nonresident Indians. Likewise, Indian health systems, long renowned for being able to deliver world-class medical outcomes at a fraction of the cost of Western hospitals, are now also fast becoming leaders in technology integration. For example, the Government of India established one of the world's first national public telemedicine consultation services (eSanjeevani), which, as of September 2021, has completed over 12 million consultations. Apollo Hospitals launched Apollo 24/7, among the world's largest, private, multichannel, digital health-care platforms, to allow mobile access to a range of services such as specialist consultations, online pharmacy, and diagnostic laboratory tests at home.[5]

India has over 600 medical colleges and some 3500 engineering colleges. Although many of them offer degrees in biomedical engineering, it is still rare for an Indian medical student or doctor to pursue a Master's or PhD degree in engineering or AI. The mindset of most medical students is to pursue the traditional path of a specialist in private practice. Changing this mindset, at least among a subset of students, will be essential to fill the talent gap needed to achieve a biomedical computing leadership role.

There are several challenges to keep in mind when developing models for interdisciplinary education in biomedical computation.[2] Training opportunities should not be prohibitively lengthy. Biomedicine and computation are each individually large and diverse fields, with many subfields of specialization. Obtaining deep knowledge in all these areas could itself take an entire career and that is before considering that knowledge in each of the fields is rapidly evolving. The jobs of today may be different from those years in the future. Training models which focus on teaching broad fundamentals, with a few depth areas, allow students to gain solid foundations while also becoming well versed in quickly learning needed knowledge and skills upon encountering an unfamiliar or emerging area of focus. Broad fundamentals also form a measure of job security – a student trained with enough depth in biomedical and/or engineering disciplines still has the safety net of a job in another established field.

Even when dual training of an individual is not possible, there are several smaller steps that can be taken to enable contributions to biomedical innovation. Travel fellowships to attend AI/digital health conferences could be offered annually to 1000 medical students chosen nationally for their aptitude. Internships at technology and venture capital companies could be offered to recent medical graduates. The Kauffman Fellows program in the US has trained 765 entrepreneurship fellows who have then founded 280 firms. Health hackathons and solutions-oriented workshops can be jointly hosted by local medical and engineering schools along with hospitals and tech companies to build a culture of innovation. Massachusetts Institute of Technology (MIT) Hacking Medicine, organized by MIT students, has organized more than 175 such events across 29 countries which have created over 50 companies and raised over $240M in venture funding.[6] One of us (PMD) has served as a judge at MIT's Hacking Medicine Grand Hack.

Talent and mindset are two key requirements for progress. In addition, India also needs to continue to encourage and build an ecosystem of innovation, including institutional frameworks, biomedical research infrastructure, and funding mechanisms to enable greater research and to translate discoveries into care innovations.[7] This will enable India to not only train but also to retain its brightest AI and digital health leaders.


AK has previously held executive and advisory roles at startups working at the interface of technology and health care. PMD has received research grants, advisory fees, and/or stock from a number of biomedical and technology companies and serves as a director of AHEL. PMD is also a co-inventor on several patents.

  References Top

Lee P, Abernethy A, Shaywitz D, Gundlapalli A, Weinstein J, Doraiswamy PM, et al. Digital Health COVID-19 Impact Assessment: Lessons Learned and Compelling Needs. NAM Perspectives. National Academy of Medicine; 2022. Available from: https://nam.edu/digital-health-covid-19-impact-assessment-lessons-learned-and-compelling-needs/. [Last accessed on 2020 Feb 21].  Back to cited text no. 1
Kaushal A, Altman RB. Wiring minds. Nature 2019;576:S62-3.  Back to cited text no. 2
Global Innovation Index 2021 Results. World Intellectual Property Organization; 2021. Available from: https://www.wipo.int/pressroom/en/articles/2021/article_0008.html#:~:text=Switzerland%20remains %20the%20world's%20leader, in%20the%20past%20three% 20 years. [Last accessed on 2020 Feb 21].  Back to cited text no. 3
Chahal H, Abdulla S, Murdick J, Rahkovsky I. Mapping India's AI Potential. CSET Data Brief; March 2021. Available from: https://cset.georgetown.edu/publication/mapping-indias-ai-potential/. [Last accessed on 2022 Feb 22].  Back to cited text no. 4
Sibal A, Hari Prasad K, Reddy S, Doraiswamy PM. Apollo Hospitals and Project Kavach: Insights from How India's Largest Private Health System Is Handling COVID-19. NEJM Catalyst; February 24, 2021. Available from: https://catalyst.nejm.org/doi/full/10.1056/CAT.20.0677. [Last accessed on 2022 Feb 22].  Back to cited text no. 5
MIT Hacking Medicine – Democratizing Healthcare Innovation. https://hackingmedicine.mit.edu/about/. [Last accessed on 2020 Feb 21].  Back to cited text no. 6
Panda B. Establishing India's Apple. The Hindu; January 2022. Available from: https://www.thehindu.com/opinion/op-ed/establishing-indias-apple/article38261858.ece. [Last accessed on 2022 Feb 22].  Back to cited text no. 7


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