The vision for Centre for Digital Technologies in Healthcare (CDiTH) is to improve the efficacy and affordability of healthcare delivery in India and beyond by leveraging modern technologies and related academic research. It was inaugurated by Dr. D. Nageshwar Reddy, Chairman & Chief of Gastroenterology, AIG Hospitals, on 19th of March, 2025 at IIIT Hyderabad, in the august presence of Sri. Srini Raju (Chairman, iLabs Group) and Prof. P J Narayanan (Director, IIIT Hyderabad). We aim to accomplish this through following focused actions.
We aim to accomplish this through following focused actions.
- We build solutions leveraging Digital Technology covering private and public health care covering diagnosis, clinical and operational areas. Digital technology includes all aspects of AI, Digitization, Analytics, Devices, Integration etc.
- We cultivate & grow an ecosystem of partnerships across Healthcare ecosystem with the focus on collaborating on each other strengths to identify the pressing challenges & needs and overcoming & accomplishing them.
- We catalyse research & innovation at the intersection of Healthcare & Technology.
We are a dedicated centre with its own Chief executive, Leadership, Research engineers and Translation Fellows. However we interact closely with the research centres within IIIT, derive immensely from the research work and expertise of centres and utilize the same for building solutions.
We are currently engaged with Private Health Institutions and NGOs and are working on building solutions for curated needs. Each of the project that we are working on has a clear path to deployment and value realization, which is a key criteria for project selection. We identify the needs in close collaboration with our partners who experience them and work with them to qualify, define & elaborate the problem statement. We strive to build robust and deployable solutions for the immediate need of partner and beyond.
We are also working on establishing a Centre of Excellence for facilitating deployment of models on the ground in Healthcare space. This effort involves validating & verifying the robustness & readiness of the AI models. This would not only review the strength of evidence and alignment of datasets tested with target demographics, but also enable testing of the model on more appropriate datasets and intended to provide a framework to ensure regular monitoring even post deployment.