Artificial intelligence is set to play a transformative role in healthcare by improving diagnosis, widening access to medical services, and supporting clinical decision-making, but human judgment, ethics, and accountability must remain indispensable, experts said during the AI Manthan 2.0 healthcare session at Chhatrapati Shahu Ji Maharaj University.
The Breast Cancer Screening Model Presented at This AI Manthan 2.0 Healthcare Session
Prof Malay Kishore Dutta from Amity University, Noida, highlighted advances in AI-powered healthcare, and also presented a low-cost AI-based breast cancer screening model using blood biomarkers, aimed at improving access to early detection in rural and underserved areas.
Why a Blood Biomarker-Based Approach Matters for Rural Access
Building a screening model around blood biomarkers rather than imaging-based diagnostics like mammography could meaningfully lower the infrastructure and cost barriers that have historically limited early breast cancer detection access in rural and underserved regions, where imaging equipment and trained radiologists are often scarce.
The Call for Medical Education Reform Within This AI Manthan 2.0 Healthcare Session
Former professor at the Indian Institute of Health Management Research Suptendra Nath Sarbadhikari stressed that AI should support, not replace, clinicians. He called for integrating AI and digital health training into medical education, emphasizing that future doctors must understand both the strengths and limitations of AI systems.
Why Understanding Both Strengths and Limitations Matters
Sarbadhikari’s specific emphasis on training future doctors to understand AI’s limitations alongside its strengths suggests a concern that medical education focused solely on AI’s capabilities, without equal attention to where and how these systems can fail, could leave the next generation of clinicians less equipped to catch and correct AI errors in practice.
The Caution Against Over-Reliance Within This AI Manthan 2.0 Healthcare Session
Prof Krithika Rangarajan from AIIMS, New Delhi, cautioned against over-reliance on automated tools, noting that while AI can enhance efficiency and even appear empathetic, it can also reinforce incorrect assumptions if not properly supervised.
Why AI Appearing “Empathetic” Complicates This Caution
Rangarajan’s specific observation that AI tools can “appear empathetic” adds a notable dimension to the standard over-reliance warning, suggesting that AI’s ability to mimic emotionally attuned communication could make clinicians and patients more likely to trust its outputs even when the underlying reasoning is flawed or based on incorrect assumptions.
Radiology as a Model of Responsible AI Adoption Within This AI Manthan 2.0 Healthcare Session
Dr Vasantha Kumar Venugopal from Rajiv Gandhi Cancer Institute, New Delhi, highlighted radiology as an example of responsible AI adoption, where technology assists doctors while preserving clinical oversight.
Why Radiology Serves as a Useful Template
Radiology’s longer track record of AI integration, spanning image analysis and pattern detection tools that have been refined over several years, gives Venugopal’s example added credibility as a template other clinical specialties considering AI adoption might study, since it demonstrates how technology assistance and clinician oversight can coexist in an established, real-world workflow.
What This AI Manthan 2.0 Healthcare Session Means Going Forward
Given the consistent theme across all four speakers, that AI should augment rather than replace clinical judgment, medical institutions considering AI curriculum integration may find Sarbadhikari’s specific call for embedding AI and digital health training into medical education a practical starting point for reform. Given Dutta’s rural-focused breast cancer screening model, health systems and policymakers in underserved regions may find blood biomarker-based AI screening tools a more immediately scalable early-detection strategy than imaging-dependent alternatives.
What to Watch Going Forward
As Indian medical institutions continue exploring AI integration following discussions like this AI Manthan 2.0 healthcare session, industry observers will likely watch whether Dutta’s low-cost breast cancer screening model advances toward broader rural deployment, and whether medical schools begin formally incorporating the AI and digital health training Sarbadhikari called for. Given Rangarajan’s specific warning about AI’s capacity to reinforce incorrect assumptions when unsupervised, this AI Manthan 2.0 healthcare session may contribute to a broader, ongoing conversation within Indian healthcare institutions about building the supervisory and educational safeguards needed to adopt AI responsibly across diverse clinical settings.
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