An innovative self-supervised learning framework developed for real-time detection of Freezing of Gait (FoG) in Parkinson's Disease (PD) patients, using a single triaxial accelerometer
This paper is enriched with detailed discussions of the contributions toward robustness and explainability in digital health, the development of trustworthy AI systems in the era of LLMs, and various evaluation metrics for measuring trust and related parameters such as validity, fidelity, and diversity.
A comprehensive survey introducing the first cross-domain framework and taxonomy for agentic LLM systems in biology, spanning genomics to clinical imaging and highlighting key evaluation challenges.
A comprehensive review on AI-powered wearable biosensors, highlighting how machine learning and edge AI enable real-time health monitoring and personalized care. The paper discusses key innovations like digital twins and LLMs, along with challenges in privacy, scalability, and clinical integration..
Developed a method for diagnosis and severity assessment of PD using a model based on Gramian Angular Fields in combination with deep Convolutional Neural Networks (CNNs)