output
20172022
most citedFederated Learning Enables Big Data for Rare Cancer Boundary Detection

390 citations

5 papers

cs.LG2022★ 390 cited

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Sarthak Pati, Ujjwal Baid, Brandon Edwards +276

Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…

cs.LG2021★ 15 cited

Co-occurrence of medical conditions: Exposing patterns through probabilistic topic modeling of SNOMED codes

Moumita Bhattacharya, Claudine Jurkovitz, Hagit Shatkay

Patients associated with multiple co-occurring health conditions often face aggravated complications and less favorable outcomes. Co-occurring conditions are especially prevalent a…

eess.IV2021★ 16 cited

The Federated Tumor Segmentation (FeTS) Challenge

Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29

This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…

q-bio.QM2017

Assessing Chronic Kidney Disease from Office Visit Records Using Hierarchical Meta-Classification of an Imbalanced Dataset

M. Bhattacharya, C. Jurkovitz, H. Shatkay

Chronic Kidney Disease (CKD) is an increasingly prevalent condition affecting 13% of the US population. The disease is often a silent condition, making its diagnosis challenging. I…

stat.AP2017★ 5 cited

Identifying Growth-Patterns in Children by Applying Cluster analysis to Electronic Medical Records

Moumita Bhattacharya, Deborah Ehrenthal, Hagit Shatkay

Obesity is one of the leading health concerns in the United States. Researchers and health care providers are interested in understanding factors affecting obesity and detecting th…