AI Healthcare Conference at IIIT Delhi: Bridging Medicine And Engineering

AI algorithms can analyze medical images (like X-rays, MRIs, and CT scans) with high accuracy, often matching or surpassing the performance of radiologists
AI can predict patient outcomes by analyzing large datasets, helping in early diagnosis and personalized treatment plans. Predictive models can forecast disease progression, patient readmissions, and potential complications. (Representational Image: Unsplash)
AI can predict patient outcomes by analyzing large datasets, helping in early diagnosis and personalized treatment plans. Predictive models can forecast disease progression, patient readmissions, and potential complications. (Representational Image: Unsplash)
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AI refers to the simulation of human intelligence in machines programmed to think and learn, encompassing tasks such as problem-solving, reasoning, and understanding language. In healthcare, AI has the potential to significantly improve patient care.

On September 5, 2024, a day-long conference was held at iHub Anubhuti IIITD Foundation of the Indraprastha Institute of Information Technology Delhi (IIIT Delhi). The event focused on AI in healthcare, aiming to bridge the gap between medicine and engineering. Professor Abhay Karandikar, Secretary of the Department of Science and Technology (DST), highlighted the potential of the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS). He emphasised how integrating AI, clinical sciences, and basic sciences could harness India’s vast data to enhance healthcare accessibility.

Over the next three years the NM-ICPS aims to recalibrate and synchronize efforts to achieve impactful advancements

Professor Abhay Karandikar, Secretary Department of Science and Technology (DST)

The conference underscored the need for interdisciplinary collaboration to address the country's data surplus. Organized by DST and five technology innovation hubs (TiHs) established under NM-ICPS, and co-supported by AIIMS Delhi, the conference sought to identify key healthcare challenges, foster interdisciplinary collaboration, and explore practical implementations.

Participants were encouraged to provide recommendations to enhance the effectiveness of healthcare interventions. The event featured notable attendees, including Dr. Ranjan Bose, Director of IIIT Delhi; Dr. Ekta Kapoor, Head of FFT Division, DST; Dr. Pushpendra Singh and Dr. Vikram Goyal, Project Directors at iHub Anubhuti-IIITD Foundation; and other domain experts.

AI aids in tailoring treatment plans to individual patients based on their genetic makeup, lifestyle, and health history. This approach improves the effectiveness of treatments and reduces adverse effects. (Representational Image: Unsplash)
AI aids in tailoring treatment plans to individual patients based on their genetic makeup, lifestyle, and health history. This approach improves the effectiveness of treatments and reduces adverse effects. (Representational Image: Unsplash)

Distinguished professionals included Dr. Sandeep Aggarwal, Chairman of the Institute of Minimal Access, Bariatric, GI and Robotic Surgery, Manipal Hospitals, New Delhi; Dr. Sanjeev Sinha from AIIMS Delhi; Dr. Saket Choudhary from the Koita Centre for Digital Health, IIT Bombay; Dr. Moushumi Suryavanshi from the Amrita Institute of Medical Sciences, Faridabad; Dr. Anurag Agarwal from the Koita Center for Digital Health, Ashoka University; and Dr. Bharat Aggarwal, Principal Director of Radiology at Max Hospitals, Delhi.

We will be able to launch an interdisciplinary R&D program which will work at the intersection of engineering, basic sciences, computer scientists, and also the practicing doctors and clinicians,

Professor Abhay Karandikar, Secretary Department of Science and Technology (DST)

The conference included interactive panel discussions on "Perspective of AI in Healthcare from the Medical Community" and "Perspective of AI in Healthcare from the Engineering Community," as well as a visit to the Medical Cobotics Center (MCC), providing attendees with a comprehensive understanding of AI’s potential in healthcare.

(Input from various sources)

(Rehash/Yash Kamble/MSM)

AI can predict patient outcomes by analyzing large datasets, helping in early diagnosis and personalized treatment plans. Predictive models can forecast disease progression, patient readmissions, and potential complications. (Representational Image: Unsplash)
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