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Evidence record 4945 · automatically gathered

FairHealth: An Open-Source Python Library for Trustworthy Healthcare AI in Low-Resource Settings

We present FairHealth, an open-source Python library that provides a unified, modular framework for trustworthy machine learning in healthcare applications, with particular focus on low-resource and low-income country (LMIC) settings such as Bangladesh. FairHealth addresses four critical gaps in existing healthcare AI toolkits: (1) the absence of integrated fairness auditing for biosignals and clinical tabular data; (2) the lack of privacy-preserving federated learning tools compatible with stan

Record details

Published: 5 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Privacy · Healthcare · Transparency
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (5 May 2026), “FairHealth: An Open-Source Python Library for Trustworthy Healthcare AI in Low-Resource Settings,” evidence record 4945, https://ethics.ai/record/4945 (originally published by arXiv).

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