NIMS, IISc Join Forces to Develop AI Tools for Early Disease Detection & Personalised Healthcare
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The first phase will focus on analysing clinical datasets, designing AI algorithms, and developing preliminary models that can support future clinical applications.
NIMS Hyderabad and IISc Bengaluru have launched a joint AI research initiative to build healthcare tools for early diagnosis, risk assessment, and personalised treatment of cancer, kidney disease, heart conditions, and obesity.
The first phase, expected to be completed within six months, will focus on analysing clinical datasets, designing AI algorithms, and developing preliminary models that can support future clinical applications.
"Beyond improving diagnostic speed and accuracy, these AI models will be designed to support clinical decision-making and enhance the accessibility of medical services for the general public," Dean of NIMS, Dr P Chandrasekhar, said.
According to NIMS, the long-term objective is to develop AI systems that can be integrated into real-world healthcare settings while addressing the unique characteristics of Indian patient populations.
The partnership builds on discussions held earlier between senior officials from NIMS, representatives of the TANUH Foundation, and the Artificial Intelligence Centre of Excellence in Healthcare at IISc.
Those discussions outlined a broader vision that includes multi-centre AI healthcare studies, clinical data-driven research, precision medicine, and translational AI applications capable of moving innovations from research laboratories into hospitals.
Both institutions have also expressed interest in establishing a long-term strategic partnership that combines clinical expertise with advanced scientific research.
The collaboration is expected to encourage the development of AI-driven healthcare technologies that can be deployed across hospitals, improve patient outcomes, and strengthen India's digital health ecosystem.
Earlier, NIMS partnered with IIT Hyderabad to release an open-source pathology dataset containing digitised histopathological images of brain cancer and lupus nephritis.
The resource forms part of the India Pathology Dataset (IPD) project, an initiative designed to accelerate AI research in pathology by bringing together hospitals, academic institutions, industry, and government organisations.
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