5 citations · 8 across the 4 of their papers we have counts for
5 papers
Adaptive Bayesian Partner Selection for Federated Clinical Centers
Navid Seidi, Satyaki Roy, Sajal K. Das
Federated learning (FL) in healthcare faces pronounced heterogeneity and temporal concept drift across clinical centers, where evolving patient populations and care practices shift…
Enhancing Federated Survival Analysis through Peer-Driven Client Reputation in Healthcare
Navid Seidi, Satyaki Roy, Sajal Das
Federated Learning (FL) holds great promise for digital health by enabling collaborative model training without compromising patient data privacy. However, heterogeneity across ins…
Addressing Data Heterogeneity in Federated Learning of Cox Proportional Hazards Models
Navid Seidi, Satyaki Roy, Sajal K. Das +1
The diversity in disease profiles and therapeutic approaches between hospitals and health professionals underscores the need for patient-centric personalized strategies in healthca…
A Stable Matching Assignment for Cancer Treatment Centers using Survival Analysis
Navid Seidi
The treatment of cancer is one of the most discussed issues in the realm of contemporary public health research. One of the primary concerns of both the general public and the gove…
Using Geographic Location-based Public Health Features in Survival Analysis
Navid Seidi, Ardhendu Tripathy, Sajal K. Das
Time elapsed till an event of interest is often modeled using the survival analysis methodology, which estimates a survival score based on the input features. There is a resurgence…