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What happens when treatment decisions are no longer driven only by clinical experience, but also by predictive intelligence and real-time data insights?

Can healthcare systems continue relying on traditional treatment pathways when AI is beginning to reshape how therapies are designed, personalized, and optimized?

Healthcare is moving toward a future where AI driven treatment systems are enabling more precise, adaptive, and outcome-focused care.

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Precision Treatment Systems

AI is enabling more targeted and patient-specific treatment approaches by analyzing clinical, genomic, and real-world health data.

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Predictive Clinical Intelligence

AI driven systems are helping clinicians anticipate treatment responses and optimize therapy decisions before interventions are made.

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WHY THIS TRACK AT HAI CONCLAVE 2026?

Are current treatment systems still enough in an era where AI is starting to predict, personalize, and optimize cancer care at scale?

According to MarketsandMarkets, one of the rapidly growing segments within AI-driven treatment innovation is the AI in Oncology market, projected to grow from USD 2.45 Billion (2024) to USD 11.52 Billion (2030), at a CAGR of 29.4%. This rapid growth signals a clear transformation in treatment paradigms—from standardized protocols to AI-enabled precision, personalization, and outcome-driven care.

As this shift accelerates, HAI Conclave 2026 brings together healthcare leaders, clinicians, researchers, and innovators to explore the future of AI-powered treatment systems.

  • AI-enabled precision and personalized treatment pathways
  • Predictive models supporting clinical decision-making
  • Oncology focused AI applications transforming care delivery
  • Data-driven optimization of treatment outcomes
WHAT THIS TRACK COVERS?

01

AI in Oncology & Precision Medicine

Explore how AI is transforming cancer care through early prediction, treatment personalization, and therapy optimization.

02

Predictive Treatment Decision Systems

Understand how AI models assist clinicians in selecting more effective treatment pathways based on patient-specific data.

03

Personalized Therapy Design

Learn how AI enables individualized treatment strategies using genomic, clinical, and behavioral data integration.

04

Outcome Driven Treatment Optimization

Discover how AI continuously evaluates treatment effectiveness to improve patient outcomes over time.

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25+

Industry Partners

300+

Clinicians, Founders, Investors, Corporates, Hospital Leadership

150+

Speakers

100+

Abstract Submissions

25+

Startups

6+

Focus Tracks
SPEAKERS
Dr. Chirag Thonse
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Chirag Thonse

Manipal Hospital

Dr. Chinnababu S
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Chinnababu S

Yashoda Hospitals

Dr. Purvish Parikh
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Purvish Parikh

Shalby Cancer & Research Institutes

Pramod S Chinder
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Pramod S Chinder

HCG Cancer Center

sponsors
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Ramesh Bilimagga

Radiation Oncologist, HCG Cancer Center

Dr. Raj Nagarkar
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Raj Nagarkar

HCG Manavata Cancer Center

Rohitt Mahajan
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Rohitt Mahajan

Intuitive

Lt. Gen. Ananthanarayan Arun
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Lt. Gen. Ananthanarayan Arun

Retired Indian Army

Dr. Amrut Sadashiv Kadam
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Amrit S Kadam

Victoria Hospital

Justin-Harrison
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Justin Harrison

You, Only Virtual

Krithika Sekhar
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Krithika Sekhar

HCG Cancer Center

Lohit Reddy
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Lohit Reddy

HCG Cancer Center

Dr. Kumara Swamy
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Kumaraswamy

MD, Clinical Research Scientist Oncology HCG Cancer Center

sponsors
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Dr. A Pichandi

Director, Central Physics, HCG Cancer Center

Peddi Shanmukh Srinivas
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Peddi Shanmukh Srinivas

Theranautilus

Rajarajan
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Rajarajan

Alluri Sitarama Raju Academy of Medical Sciences

sponsors
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Shravan Subramanyam

Managing Director & Group CEO BPL Medical Technologies

ESTEEMED PARTNERS
ASSOCIATION PARTNERS
TECHNOLOGY PARTNERS
FAQ SECTION

AI is enabling more precise, predictive, and personalized treatment decisions by analyzing patient data and improving clinical decision-making.

AI in oncology uses machine learning and predictive models to improve cancer detection, treatment planning, and therapy optimization.

No. AI supports clinicians by providing data-driven insights that improve accuracy and efficiency in treatment planning.

Oncologists, clinicians, healthcare leaders, AI researchers, medical innovators, and professionals working in advanced treatment systems.