India AI Impact Summit 2026

ai-for-societal-value-responsible-innovation-across-healthcare-and-high-impact-sectors

5 min read

TRACK:Safe and Trusted AI
SPEAKERS
  • Dr. Arif Ahmed Sekh, UiT The Arctic University of Norway
  • Dr. Gunjan Gupta Govil, Gunjan IVF World and a fertility specialist
  • Dr. Kiran D. Sekhar, Kiran Fertility Clinics
  • Dr. Swarupa Mitra, Fortis Medical
  • Dr. Tanuj Bhatia, SGRR Medical College & SMI Hospital
  • Prof. Dilip K. Prasad, UiT The Arctic University of Norway
SESSION OVERVIEW

This session explores how artificial intelligence is reshaping healthcare and other high-impact sectors as it moves from research to real-world deployment. It examines pathways for responsible innovation, sustainable commercialization, and long-term societal value, while addressing ethical considerations, regulatory readiness, and trust. Through forward-looking perspectives, the discussion highlights how AI systems can be designed, governed, and scaled to deliver meaningful impact without compromising transparency, fairness, or accountability.

VIDEO RECORDING

AI for Societal Value: Responsible Innovation Across Healthcare and High-Impact Sectors

Abstract

The panel examined how artificial intelligence is transitioning from research labs to real‑world clinical settings, with a focus on cardiology, oncology, and reproductive medicine. Participants highlighted concrete AI‑driven tools that accelerate diagnosis, enable preventive care, and democratize access, while also flagging privacy, ethical, and regulatory challenges that must be addressed for responsible, trustworthy deployment.

Detailed Summary

  • Prof. Dilip Prasad welcomed the audience and introduced the panelists.
  • Dr. Arif Ahmed Sekh gave a brief opening remark, positioning AI as a “big event” for societal value.

2. AI in Cardiology – From Reactive to Preventive (5:00‑15:00)

  • Speaker: Dr. Tanuj Bhatia (referred to as “Dr. Tanur” in the transcript).
  • Key points:
    • Early 2000s: AI used to flag ST‑elevation on ECGs, shortening door‑to‑balloon time in acute MI.
    • AI now enables prediction of myocardial infarction risk and death events, moving cardiology toward primary prevention.
    • Optical Coherence Tomography (OCT) integrated with AI can delineate arterial lumen, guide precise stent sizing, and support a mechanistic approach to coronary syndromes.
    • Penumbra (computer‑assisted vacuum device) uses auditory/visual AI cues to alert operators, reducing fatigue‑related errors.

3. AI in Oncology – Diagnosis, Personalisation & Operations (15:00‑25:00)

  • Speaker: Dr. Swarupa Mitra.
  • Key points:
    • AI tools enable early cancer detection even in remote settings.
    • Rapid, accurate diagnosis shortens the critical time‑to‑treatment window.
    • Personalised therapy: AI integrates genomics, imaging, pathology, and EMR data to tailor regimens per patient.
    • AI shortens operative times (e.g., surgery reduced from 7–8 hrs) and improves radiation planning by targeting tumours while sparing healthy tissue.
    • AI predicts toxicity risk, allowing pre‑emptive mitigation.
    • Operational impact: AI‑driven scheduling and bed‑allocation reduce OPD queues and optimise resource use.

4. AI in Reproductive Medicine – From Ovulation Tracking to Embryo Selection (25:00‑35:00)

  • Speaker: Dr. Kiran D. Sekhar.
  • Key points:
    • AI‑based mobile tools allow patients to log symptoms and track ovulation from home.
    • Personalised ovarian stimulation: AI recommends gonadotropin dosages based on age, hormone profile, and follicle count, increasing mature egg yield.
    • Oocyte maturity assessment: AI analyses microscopy images to objectively grade oocyte quality, replacing subjective visual checks.
    • Embryo monitoring: Time‑lapse “embryoscope” captures images every 10 min, delivering a continuous developmental video that AI evaluates for implantation potential.
    • Embryo selection: AI predicts the best embryo with ~97 % accuracy, akin to a “beauty‑pageant” ranking, reducing human bias.

5. Democratising Cardiac Care – Tele‑Cardiology & Remote Diagnostics (35:00‑45:00)

  • Speaker: Dr. Tanuj Bhatia (follow‑up).
  • Key points:
    • AI‑accelerated echocardiography now produces interpretable results in 13–15 seconds vs. ~40 minutes previously.
    • Strain‑tracking & speckle‑tracking detect early chemotherapy‑induced cardiotoxicity before functional decline.
    • Big O‑Health platform links remote clinics to tertiary centres via video consults, enabling rapid AI‑assisted diagnosis and timely referral.

6. AI‑Guided Structural Interventions – Virtual Reality & 3‑D Planning (45:00‑55:00)

  • Speaker: Dr. Tanuj Bhatia (continuation).
  • Key points:
    • Virtual‑reality 3‑D reconstructions of CT scans allow simulation of complex procedures (e.g., trans‑catheter aortic valve replacement, left‑atrial appendage closure).
    • Case study: a rare left‑atrial appendage aneurysm (one of ~200 historic cases) was successfully managed using AI‑driven 3‑D modelling to anticipate complications.
    • AI provides patient‑specific procedural planning, reducing intra‑operative surprises.

7. Clinical‑Trial & Data‑Privacy Challenges (55:00‑1:05:00)

  • Speaker: Dr. Tanuj Bhatia (research‑director perspective).
  • Key points:
    • Conducting RCTs with AI is hampered by data‑privacy concerns; most AI solutions rely on cloud platforms.
    • Generalisation risk: AI models trained on Western cohorts may not transfer to South‑Asian populations.
    • Black‑box problem: lack of interpretability may lead to over‑reliance on opaque predictions.
    • Example: HF‑CORE trial demonstrated AI‑predicted heart‑failure onset, but scaling to the masses remains a hurdle.

8. Ethical & Legal Considerations in Oncology & Reproduction (1:05‑1:15:00)

  • Speaker: Dr. Swarupa Mitra (ethical focus).
  • Key points:
    • Informed consent must explicitly state AI involvement and its limitations.
    • Algorithmic bias: training data must be diverse to avoid skewed outcomes.
    • Equity: AI should not preferentially serve affluent or urban patients.
    • Human‑in‑the‑loop principle: clinicians retain ultimate decision‑making authority.

9. Audience Q&A – Rapid‑Response AI in the Cath Lab (1:15‑1:25:00)

  • Questions:
    • How AI reduces unnecessary cath‑lab activations (from 42 % to 8 % in a cited study).
    • Use of AI‑enabled FFR‑CT for non‑invasive stenosis assessment.
    • Role of AI‑driven OCT for lesion sizing and treatment decision.

10. Closing Remarks – Societal Impact & Future Outlook (1:25‑1:35:00)

  • Speakers: Dr. Swarupa Mitra, Dr. Kiran Sekhar, Dr. Tanuj Bhatia.
  • Consensus:
    • AI must augment—not replace—clinicians.
    • Proper training of physicians in AI literacy is essential.
    • When responsibly deployed, AI can lower costs, reduce burnout, and expand access to high‑quality care.

Key Takeaways

  • Preventive cardiology: AI enables early MI risk prediction, shifting treatment from reactive to preventive.
  • Oncology personalization: AI integrates multi‑modal data (genomics, imaging, pathology) to tailor therapies and predict toxicities.
  • Reproductive breakthroughs: AI improves ovulation tracking, individualized stimulation dosing, objective oocyte grading, and embryo selection with ~97 % accuracy.
  • Speed & scalability: AI reduces echocardiogram interpretation to seconds, accelerates OCT‑based stent planning, and shortens surgery times.
  • Remote care democratization: Tele‑cardiology platforms linked with AI bring specialist diagnostics to underserved regions.
  • Clinical‑trial barriers: Data privacy, population bias, and black‑box opacity hinder robust evaluation of AI tools.
  • Ethical safeguards: Transparent consent, diverse training data, equity of access, and maintaining a human‑in‑the‑loop are non‑negotiable.
  • Regulatory readiness: AI devices need clear regulatory pathways; clinicians must stay informed about evolving guidelines.

End of summary.

See Also:

Graph View

Backlinks