Federated Learning for Privacy-Preserving At-Risk Student Prediction in Health Professional Education: A Multi-Scenario Evaluation of FedAvg and FedProx
Publication date: Available online 7 August 2026 Source: Computers and Education: Artificial Intelligence Author(s): Daniel Kwasi Kovor, Eric Opoku Osei, Ebenezer Nana Agyemang
Record details
Published: 9 August 2026
Source: Computers and Education: Artificial Intelligence
Category: Research
Topics: Privacy · Healthcare · Children & education
Retrieved: 9 August 2026
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How to cite this record
ethics.ai (9 August 2026), “Federated Learning for Privacy-Preserving At-Risk Student Prediction in Health Professional Education: A Multi-Scenario Evaluation of FedAvg and FedProx,” evidence record 17708, https://ethics.ai/record/17708 (originally published by Computers and Education: Artificial Intelligence).
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