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38 papers in the last four weeks, up 41% on the four weeks before. 0.3% of all new papers.

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Bridging the Version Gap: Multi-version Training Improves ICD Code Prediction, Especially for Rare Codes
May 18, 2026Jinghui Liu, Anthony NguyenAutomated Medical Coding Healthcare
Australian e-Health Research Centre, CSIRO
A World Model of Radiologist Reading for Medical Image Representation Learning
May 17, 2026Yiwei Li, Zihao Wu, Huaqin Zhao +5World Model Learning Healthcare
University of Georgia · University of Texas at Arlington · New Jersey Institute of Technology
Medical Context Distorts Decisions in Clinical Vision Language Models
May 17, 2026David Restrepo, Ira Ktena, Maria Vakalopoulou +2VLM Evaluation VLM Robustness
1MICS, CentraleSup´elec - Universit´e Paris-Saclay, France · 2Cancer Data Science Unit, IHU PRISM, National Institute in Precision Oncology, University Paris-Saclay, CentraleSupelec, Gustave Roussy, INSERM, Gif-sur-Yvette · 3Ellison Institute of Technology (EIT), Oxford, UK +1
BELIEF: Structured Evidence Modeling and Uncertainty-Aware Fusion for Biomedical Question Answering
May 17, 2026Chang Zong, Hao Ning, Siliang Tang +2Healthcare Evidence-Grounded Reasoning
School of Computer Science and Technology, Zhejiang University of Science and Technology, Hangzhou 310023, China · College of Artificial Intelligence, Zhejiang University, Hangzhou 310027, China · Zhejiang Key Laboratory of Biomedical Intelligent Computing Technology, Zhejiang University of Science and Technology, Hangzhou 310023, China
SEMA-RAG: A Self-Evolving Multi-Agent Retrieval-Augmented Generation Framework for Medical Reasoning
May 16, 2026Yongfeng Huang, Ruiying Chen, James ChengRetrieval-Augmented Generation Healthcare
CSE, The Chinese University of Hong Kong · Wuhan University of Technology
Adversarial Fragility and Language Vulnerability in Clinical AI: A Systematic Audit of Diagnostic Collapse Under Imperceptible Perturbations and Cross-Lingual Drift in Low-Resource Healthcare Settings
May 16, 2026Anthonio Oladimeji Gabriel, Ahmad Rufai YusufMultilingual Language Model Evaluation Healthcare
Centre for Clinical Intelligence & Safety, Ìyàwó, Nigeria · Tomorrow University of Applied Sciences, Germany
From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction
May 16, 2026Pujun Feng, Xiaoyu Guo, Seyed Ehsan Saffari +10Causal Effect Estimation Off-Policy Evaluation
Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR 999078, China. · Medin.ai, Beijing 100871, China. · School of Software & Microelectronics, Peking University, Beijing 100871, China. +8
CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?
May 15, 2026Haolin Chen, Deon Metelski, Leon Qi +30Healthcare Long-Horizon Agent Evaluation
Johns Hopkins Medicine · Wellstar Health System · Stanford University +16
MedMIX: Modality-Internal Expert Fusion for Multimodal Medical Diagnosis
May 15, 2026Seungik Cho, Anqi Li, Wei QiuMissing-Modality Learning Multimodal Robustness
Department of Electrical and Computer Engineering Rice University Houston, TX 77005
Symphony for Speech-to-Text: Supporting Real-Time Medical Voice Interfaces
May 15, 2026Arne Nix, Robert James, Lasse Borgholt +6Healthcare Streaming ASR
Corti
Fully Open Meditron: An Auditable Pipeline for Clinical LLMs
May 15, 2026Xavier Theimer-Lienhard, Mushtaha El-Amin, Fay Elhassan +5Healthcare LLM Auditing
LiGHT, EPFL
BiomedAP: A Vision-Informed Dual-Anchor Framework with Gated Cross-Modal Fusion for Robust Medical Vision-Language Adaptation
May 15, 2026Huanyang Tong, Kai Liu, Fangjun Kuang +1VLM Robustness Prompt Learning
Wenzhou University · Wenzhou Business College
Few-Shot Large Language Models for Actionable Triage Categorization of Online Patient Inquiries
May 15, 2026Liqi Zhou, Jiafu LiHealthcare Clinical Triage
MHGraphBench: Knowledge Graph-Grounded Benchmarking of Mental Health Knowledge in Large Language Models
May 15, 2026Weixin Liu, Congning Ni, Shelagh A. Mulvaney +4LLM Evaluation Healthcare
Vanderbilt University, Nashville, TN, USA · Vanderbilt University Medical Center, Nashville, TN, USA · Virginia Tech, Blacksburg, VA, USA
MI-CXR: A Benchmark for Longitudinal Reasoning over Multi-Interval Chest X-rays
May 15, 2026Sunghwan Steve Cho, Yunseok Han, Jaeyoung DoVLM Evaluation Healthcare
AIDAS Laboratory, 1ECE & 2IPAI, Seoul National University
RoiMAM: Region-of-Interest Medical Attention Model for Efficient Vision-Language Understanding
May 15, 2026Jiayan Yang, Zhuoyu Wu, Wenqi FangHealthcare Efficient VLM Inference
Shenzhen Institutes of Advanced Technology, Chinese Academy of Science · CyPhi(ΨΦ) AI Research Lab, School of IT, Monash University, Malaysia Campus
Retrieval-Augmented Large Language Models for Schema-Constrained Clinical Information Extraction
May 14, 2026A H M Rezaul Karim, Ozlem UzunerRetrieval-Augmented Generation Healthcare
George Mason University, VA, USA
Text Knows What, Tables Know When: Clinical Timeline Reconstruction via Retrieval-Augmented Multimodal Alignment
May 14, 2026Sayantan Kumar, Shahriar Noroozizadeh, Juyong Kim +1Multimodal RAG Healthcare
Division of Intramural Research National Library of Medicine, National Institutes of Health Bethesda, MD, USA
COTCAgent: Preventive Consultation via Probabilistic Chain-of-Thought Completion
May 14, 2026Zihan Deng, Xiaozhen Zhong, Chuanzhi XuHealthcare Clinical Decision Support
School of Computing and Data Science, The University of Hong Kong · 2Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China · School of Computer Science, The University of Sydney
Quantifying and Mitigating Premature Closure in Frontier LLMs
May 14, 2026Rebecca Handler, Suhana Bedi, Nigam ShahHealthcare LLM Prompting
Department of Medicine, Stanford University · Department of Biomedical Data Science, Stanford University
RxEval: A Prescription-Level Benchmark for Evaluating LLM Medication Recommendation
May 14, 2026Shuhao Chen, Weisen Jiang, Changmiao Wang +4Healthcare Clinical Decision Support
The Hong Kong University of Science and Technology · Southern University of Science and Technology · The Chinese University of Hong Kong +2
Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity
May 14, 2026Abolfazl Zarghani, Amir MalekesfandiariHealthcare Neuro-Symbolic Reasoning
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
DT-Transformer: A Foundation Model for Disease Trajectory Prediction on a Real-world Health System
May 14, 2026Yunying Zhu, Andrew R Weckstein, Kueiyu Joshua Lin +1Healthcare Clinical Prediction
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA · Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA · Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, MA, USA +2
Reinforcement Learning for Tool-Calling Agents in Fast Healthcare Interoperability Resources (FHIR)
May 13, 2026Marius S. Knorr, Robert Müller, Jan P. Bremer +1Healthcare RL for Language Model Reasoning
IDM gGmbH, University Medical Center Hamburg-Eppendorf, Hamburg, Germany · Aganthos
When Evidence Conflicts: Uncertainty and Order Effects in Retrieval-Augmented Biomedical Question Answering
May 13, 2026Yikun Han, Mengfei Lan, Halil KilicogluSelective Prediction Healthcare
University of Illinois Urbana-Champaign
ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows
May 13, 2026Alvaro Lopez Pellicer, Plamen Angelov, Marwan Bukhari +3LLM Hallucination Mitigation Healthcare
School of Computing and Communications, Lancaster University · Lancaster Medical School, Lancaster University · PUC-Rio, Puc-Behring Institute for AI
JANUS: Anatomy-Conditioned Gating for Robust CT Triage Under Distribution Shift
May 13, 2026Lavsen Dahal, Yubraj Bhandari, Geoffrey Rubin +1Distribution Shift Robustness Healthcare
Center for Virtual Imaging Trials, RAI Labs, Department of Radiology, Duke University, Durham NC 27708, USA · Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA · Department of Mathematics, Trinity College of Arts & Sciences, Duke University,2026 Durham, NC 27708, USA +1
MILM: Large Language Models for Multimodal Irregular Time Series with Informative Sampling
May 13, 2026Hsing-Huan Chung, Shijun Li, Yoav Wald +3Irregular Time-Series Modeling Healthcare
University of Texas at Austin · Technion-IIT · Johns Hopkins University
MedCore: Boundary-Preserving Medical Core Pruning for MedSAM
May 13, 2026Cenwei Zhang, Suncheng Xiang, Lei YouModel Compression Image Segmentation
Shanghai Jiao Tong University Shanghai, China · Technical University of Denmark Ballerup, Denmark
RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation
May 13, 2026Chengzhi Shen, Weixiang Shen, Tobias Susetzky +8Healthcare Clinical Decision-Making
Cherise · Technical University of Munich (TUM) · TUM University Hospital +8

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Bridging the Version Gap: Multi-version Training Improves ICD Code Prediction, Especially for Rare Codes

Jinghui Liu, Anthony Nguyen

Australian e-Health Research Centre, CSIRO

Automated Medical Coding Healthcare

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Clinical coding maps clinical documentation to standardized medical codes, an essential yet time-consuming administrative task that could benefit from automation. Current models on ICD coding are typically optimized for codes from a specific ICD version. However, in reality, ICD systems evolve continuously, and different versions are adopted across time periods and regions. Moreover, ICD coding suffers from the long-tail problem, and rare code performance can be a bottleneck for developing implementable models. We examine whether it is viable to train version-independent models by combining data annotated in different ICD versions, which may help address these challenges. We add ICD-9 data to the training of a modified label-wise attention model for ICD-10 prediction, and find that despite the version mismatch, adding ICD-9 yields a 27% increase in micro F1 for 18K rare ICD codes compared to training on ICD-10 alone. On 8K frequent ICD-10 codes, the multi-version training also substantially improves macro metrics, with far fewer model parameters.