Digital Health

GATE Digital Health advances data-driven healthcare through research in:

The domain focuses on Translational Medicine, applying scientific insights to clinical practice. The work spans neuroscience, cardiology, and genetic medicine, with a long-term goal of expanding into new areas that support personalized, precise, and efficient healthcare.

Introduction

GATE Digital Health Research Domain contributes to long-term healthy living through innovations in Big Data analytics, algorithms, artificial intelligence, and digital transformation.

Its research addresses all major phases of the healthcare continuum — prevention, diagnosis, treatment, and home care.

The domain’s main focus is on Translational Medicine (TM) — the application of scientific discoveries into clinical practice to improve patient outcomes and healthcare efficiency.

Concentrated on Translational Neuroscience (TN), exploring the human brain and related diseases to advance understanding of brain structure, function, and pathology, and to translate this knowledge into clinical applications and novel therapies for neurological disorders.

The field of activity has expanded to cardiology and genetic medicine.

Focus Areas

Neuro-Hypersynchrony diseases:

Neurodevelopmental and neurodegenerative disorders

Cardiology

Gene Medicine

Remote sensing, real-time patient monitoring, and alerting for hazardous events

Virtual Patient

Brain-inspired computational architectures supporting clinical diagnostics and monitoring. The system provides a virtual patient simulation environment for testing diagnostic, corrective, or control approaches.

Targeted R&D Directions

Alzheimer’s Disease:

Ongoing work focuses on identifying new biomarkers for early diagnosis and extending these methods to other dementia types.

Multi-stable Autonomous

Neuro-dynamics:

Development of a modelling framework for autonomous systems based on physiologically informed nonlinear multi-stable models

Drug Response Prediction

Instead of molecular-scale or genetic-level analysis, the approach relies on large-scale measurements, computational models, and network dynamics.

Remote Sensing

Creation of a real-time monitoring system using remote optical sensors to detect abnormalities in vital signs and identify critical events such as SUDEP, SIDS, and central apnoea.