Federated Learning for Medical Applications - A Study on Performance and Bias with Logistic Regression on Small Datasets

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Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10825031
Citations
1
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.35
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article

Federated Learning for Medical Applications - A Study on Performance and Bias with Logistic Regression on Small Datasets

Mahima Agumbe Suresh, Palak Agarwal, Kirthika Ashokkumar, S.M. Monzurur Rahman
1 citations
Privacy-Preserving Technologies in Data
0.35
article

Federated Learning for Medical Applications - A Study on Performance and Bias with Logistic Regression on Small Datasets

Mahima Agumbe Suresh, Palak Agarwal, Kirthika Ashokkumar, S.M. Monzurur Rahman
article en
1 citations

Abstract

No abstract available for this paper.
San Jose State University (US)
Openalex Percentile: Top 30%
Privacy-Preserving Technologies in Data
0.35
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Federated Learning for Medical Applications - A Study on Performance and Bias with Logistic Regression on Small Datasets — Mahima Agumbe Suresh, Palak Agarwal, et al. · (2024) | TGRS Research Map | TGRS