mlsanityData to 14 Oct 2026

P-CAFE: Personalized Cost-Aware Incremental Feature Selection For Electronic Health Records

arXiv 2508.08646 ↗First posted 12 Aug 2025cs.AIcited by 0

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Abstract (arXiv)

Electronic Health Records (EHR) have revolutionized healthcare by digitizing patient data, improving accessibility, and streamlining clinical workflows. However, extracting meaningful insights from these complex and multimodal datasets remains a significant challenge for researchers. Traditional feature selection methods often struggle with the inherent sparsity and heterogeneity of EHR data, especially when accounting for patient-specific variations and feature costs in clinical applications. To address these challenges, we propose a novel personalized, online and cost-aware feature selection framework tailored specifically for EHR datasets. The features are aquired in an online fashion for individual patients, incorporating budgetary constraints and feature variability costs. The framework is designed to effectively manage sparse and multimodal data, ensuring robust and scalable performance in diverse healthcare contexts. A primary application of our proposed method is to support physicians' decision making in patient screening scenarios. By guiding physicians toward incremental acquisition of the most informative features within budget constraints, our approach aims to increase diagnostic confidence while optimizing resource utilization.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 16 of its 46 references that are in the map. First posted on arXiv 12 Aug 2025.

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References · 16

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4 more
  1. 2024AFS-BM: Enhancing Model Performance through Adaptive Feature Selection with Binary Maskingcited by 2
  2. 2024Binary Feature Mask Optimization for Feature Selectioncited by 2
  3. 2024Dynamic feature selection in medical predictive monitoring by reinforcement learningcited by 1
  4. 2024Optimizing Disease Prediction with Artificial Intelligence Driven Feature Selection and Attention Networkscited by 1

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