NBEMS to train doctors in AI, ML
Sonal.Srivastava@timesofindia.com 05.01.2026
The National Board of Examinations (NBEMS) has recently announced introduction of online programme in Artificial Intelligence in Medical Education for postgraduate doctors and faculty, to facilitate precision medicine in Indian medical systems, enable datadriven decision-making during public health emergencies, improve hospital management, ensure uniform quality of training, and prepare doctors for a digital future.
Furthermore, the NBEMS will soon launch a two-year fellowship for doctors to train in AI and ML in IITs. NBEMS is primarily an exam-conducting authority and does not traditionally run academic programmes. Moreover, doctors consulting large language models (LLMs) for diagnosis could create a trust deficit between patients and physicians. Against this backdrop, it is essential to examine why AI, including LLMs, is being integrated into healthcare systems and how its role is being defined.
“India produces nearly 75,000 postgraduate doctors every year, yet the country continues to face a specialist deficit estimated at 10-15 lakh. With over 17,000 hospitals spread across vastly different geographies and capacities, ensuring uniform quality of training has become challenging. AI, ML, and digital health technologies can help bridge gaps in healthcare delivery. Integrating AI in medical education is driven by two converging realities. First, healthcare delivery is becoming increasingly data-intensive—from imaging and pathology to genomics and hospital management.
Second, human cognition alone can no longer process the sheer volume of clinical data being generated daily,” says Dr Minu Bajpai, vice president, NBEMS. Reducing Human Error A global survey by Elsevier across 111 countries, covering over 3,000 physicians, found that 83% of doctors without technological literacy risk being left behind. “AI will not replace doctors, but doctors trained in the latest technology will replace those who are not. AI will reinforce and standardise clinical diagnosis. For example, digitised biopsy slides can be analysed through AI software, enabling accurate reporting even in districts without specialist pathologists. X-rays, CT scans and MRIs can be increasingly interpreted with AI assistance, reducing reporting delays and human error,” says Dr Bajpai.
AI processes genetic data, disease history, comorbidities, and lifestyle factors to suggest personalised treatment, particularly for chronic diseases such as diabetes and cancer. “Patients need different treatment pathways, and that precision is not possible without data analytics,” he adds. The NBEMS has developed modules to train doctors in AI and ML at IITs and will soon launch a fellowship that will enable doctors to learn algorithm development at premier engineering institutions.
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