arXiv AI

Medical Heuristic Learning: An LLM-Driven Framework for Interpretable and Auditable Clinical Decision Rules

arXiv:2606. 16337v1 Announce Type: new Abstract: Predictive modeling for clinical tabular data is central to clinical decision support and therefore requires not only strong predictive performance but also transparent decision logic.

arXiv AI

Jun 10

MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Clinical Tabular Prediction

arXiv:2603. 02221v2 Announce Type: replace-cross Abstract: In clinical tabular prediction, classical machine learning models with feature engineering often outperform neural methods.

By Zizheng Zhang, Yiming Li, Justin Xu, Jinyu Wang, Rui Wang, Lei Song, Jiang Bian, David W Eyre, Jingjing Fu

llms benchmarks safety

arXiv Machine Learning

Jul 22

Automatic Construction of Clinical Scoring Systems with LLM Agents

arXiv:2601. 22324v3 Announce Type: replace Abstract: Modern clinical practice relies on evidence-based guidelines implemented as compact scoring systems composed of a small number of interpretable decision rules.

By Silas Ruhrberg Est\'evez, Christopher Chiu, Mihaela van der Schaar

llms agents

arXiv AI

Jun 15

STaR-DRO: Stateful Tsallis Reweighting for Group-Robust Structured Prediction

arXiv:2604. 09737v2 Announce Type: replace-cross Abstract: Structured prediction with large language models requires outputs that are label-accurate, ontology-constrained, structurally valid, and evidence-grounded under label imbalance and heterogeneous group difficulty.

By Samah Fodeh, Ganesh Puthiaraju, Elyas Irankhah, Afshan Khan, Sreeraj Ramachandran, Linhai Ma, Srivani Talakokkul, Sarah Schellhorn

llms fine-tuning safety

arXiv AI

Jul 2

Predicting Lethal Outcome (Cause) And Understanding Key Biomarkers Linked With Acute Myocardial Infarction Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

arXiv:2607. 00472v1 Announce Type: cross Abstract: Cardiovascular disease is still one of the main causes of death around the world.

By Sagnik Ghosh

arXiv Machine Learning

Jun 3

Parallel Adaptive Multi-Objective Evolutionary Learning of Discretized Bayesian Network Classifiers for Clinical Data

arXiv:2605. 29058v2 Announce Type: replace Abstract: Bayesian Networks (BNs) are of interest from an explainable AI viewpoint, offering transparent probabilistic models for decision support.

By Damy M. F. Ha, Thalea Schlender, Yvette M. van der Linden, Peter A. N. Bosman, Tanja Alderliesten

benchmarks

arXiv AI

Jun 8

REMEDI: A Benchmark for Retention and Unlearning Evaluation in Multi-label Clinical Disease Inference

arXiv:2606. 07141v1 Announce Type: cross Abstract: Language models trained for clinical disease inference are trained on patient data, which may include sensitive and private information, and data owners may request the removal of their data from a trained model due to privacy or copyright concerns.

By Anurag Sharma, Sai Teja Chunchu, Prasenjit Mitra, Sandipan Sikdar, Koustav Rudra

llms benchmarks safety

arXiv AI

Jun 11

Tabular Foundation Models for Clinical Survival Analysis via Survival-Aware Adaptation

arXiv:2606. 12006v1 Announce Type: cross Abstract: Predicting time-to-event outcomes such as mortality is a fundamental task in clinical decision-making, commonly addressed through survival analysis.

By Minh-Khoi Pham, Luca Cotugno, Alina Sirbu, Tai Tan Mai, Martin Crane, Marija Bezbradica

fine-tuning benchmarks

arXiv AI

Jun 18

Language Models as Interfaces, Not Oracles: A Hybrid LLM-ML System for Pediatric Appendicitis

arXiv:2606. 19183v1 Announce Type: cross Abstract: Large language models (LLMs) can make clinical decision support more accessible by interpreting free-text documentation, but their direct use as diagnostic engines is limited by sensitivity to prompts, information order, and plausible but incorrect outputs.

By Soheyl Bateni, Maryam Abdolali

llms safety

arXiv Machine Learning

Jun 9

SDM-Q: Cost-Aware Staged Decision-Making for Multi-Omics Classification with Deep Q-Learning

arXiv:2605. 31014v2 Announce Type: replace Abstract: Multi-omics data provide complementary molecular characterizations of disease phenotypes and play an important role in disease diagnosis and subtype classification in precision medicine.

By Nan Mu, Yangfan Xiao, Ling Wang, Xiaoning Li, Yue Kang, Chen Zhao

reinforcement-learning

arXiv Machine Learning

1d ago

Learning Auditable Classifier Models: Source-Disjoint Tree Ensembles

arXiv:2608. 15725v1 Announce Type: new Abstract: Predictive models in clinical and regulated settings must be accurate and fully auditable.

By Srikumar Krishnamoorthy

benchmarks

arXiv AI

Jun 11

Human-Guided Agentic AI for Multimodal Clinical Prediction: Lessons from the AgentDS Healthcare Benchmark

arXiv:2602. 19502v2 Announce Type: replace Abstract: Agentic AI systems are increasingly capable of autonomous data science workflows, yet clinical prediction tasks demand domain expertise that purely automated approaches struggle to provide.

By Lalitha Pranathi Pulavarthy, Raajitha Muthyala, Aravind V Kuruvikkattil, Zhenan Yin, Rashmita Kudamala, Saptarshi Purkayastha

agents multimodal benchmarks safety

arXiv Machine Learning

Jul 20

A Transportable Threshold-Based Framework for Interpretable Classification of Medical Data

arXiv:2607. 15394v1 Announce Type: new Abstract: Black-box models limit the adoption of artificial intelligence in medicine due to their lack of interpretability and reproducibility.

By Antony Garcia, Adrian Noriega, Gabrielle Britton, Xinming Huang

benchmarks safety

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