The Indian Institute of Science (IISc) Bengaluru.
Credit: Janardhan BK/DH Photo
Bengaluru: Arca AI, a company specialising in Artificial Intelligence (AI)-driven healthcare solutions, has announced two collaborations aimed at enhancing patient care, medical education, and longevity research with Longevity India, IISc Bengaluru, and Believers Church Medical College Hospital in Kerala.
Arca AI intends to implement AI, machine learning (ML), deep learning (DL) analytics, and cloud computing to equip Longevity India with advanced tools for efficiently processing and interpreting extensive research data.
Longevity India, an initiative by IISc focused on advancing aging research, promoting healthy aging, and extending human health span, will have Arca AI as its key technology partner.
This collaboration aims to provide researchers with a robust platform to track biomarkers, analyse genetic and lifestyle patterns, and develop predictive models that contribute to advancements in healthy aging for Indians.
"This initiative is expected to accelerate breakthroughs in longevity science, opening doors to novel therapeutic strategies and precision medicine approaches. The data and analysis, purposed for federated learning, will be stored with IISc," stated Arca AI.
Deepak Saini, Professor at IISc and Convener of Longevity India, remarked, “Our collaboration with Arca AI represents a major leap forward in our efforts to decode the complexities of aging and longevity. With AI-driven analytics, we can gain deeper insights into aging mechanisms, paving the way for innovative interventions that improve quality of life.”
In addition to its partnership with Longevity India, Arca AI is collaborating with Believers Hospital in Kerala to integrate AI-driven solutions that aim to redefine patient-physician interactions, enhance clinical decision-making, streamline hospital workflows, and improve patient outcomes.
Rohit Rajan, founder of Arca AI, emphasised, “We aim to create a comprehensive health portrait for the Indian population enabled by data-driven insights. This structured framework of data can be utilised for ML/DL analysis leading to predictive modelling for community deployment.”