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20222024
most citedHandling missing values in healthcare data: A systematic review of deep learning-based imputation techniques

148 citations · 181 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.LG2024★ 4 cited

Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Biomedical Data Analysis

Siqi Li, Xin Li, Kunyu Yu +12

Clinical and biomedical research in low-resource settings often faces significant challenges due to the need for high-quality data with sufficient sample sizes to construct effecti…

cs.LG2024★ 1 cited

Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare

Mingxuan Liu, Yilin Ning, Yuhe Ke +5

The escalating integration of machine learning in high-stakes fields such as healthcare raises substantial concerns about model fairness. We propose an interpretable framework - Fa…

cs.LG2023★ 16 cited

Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches

Siqi Li, Di Miao, Qiming Wu +9

Federated learning (FL) has shown promising potential in safeguarding data privacy in healthcare collaborations. While the term "FL" was originally coined by the engineering commun…

cs.LG2023★ 7 cited

Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist

Yilin Ning, Salinelat Teixayavong, Yuqing Shang +14

The widespread use of ChatGPT and other emerging technology powered by generative artificial intelligence (GenAI) has drawn much attention to potential ethical issues, especially i…

cs.LG2022★ 148 cited

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques

Mingxuan Liu, Siqi Li, Han Yuan +7

Objective: The proper handling of missing values is critical to delivering reliable estimates and decisions, especially in high-stakes fields such as clinical research. The increas…