The article reviews existing tools for assessing clinical reasoning in large language models, identifying six key dimensions—problem representation, temporal synthesis, differential and management reasoning, counterfactual reasoning, calibrated uncertainty, and reasoning faithfulness. It finds that no single instrument covers all dimensions, with some aspects reasonably addressed while others, especially faithfulness and counterfactual reasoning, remain weakly evaluated. The authors propose combining current tools through binary rubric items, separate completeness and correctness scores, importance weighting, safety caps, temporal consistency checks, and chance‑corrected reliability reporting, and call for further design work on uncertainty, counterfactual reasoning, and faithfulness in longitudinal free‑text contexts.
By Zhangshu Joshua Jiang, Zina Ibrahim, James T. Teo
TALON is a Temporally Aware Longitudinal framework for radiology report generation that adaptively integrates variable‑length patient histories. Its Dual‑Channel Temporal Fusion Module compares each prior examination with the current one through similarity and change channels, using channel‑specific attention and a prior‑specific gate to weigh relevance and suppress redundancy. Experiments on MIMIC‑CXR demonstrate that TALON surpasses state‑of‑the‑art methods on clinical efficacy and graph‑based metrics, with performance improving as more prior examinations are available.
By Nien-Tsyr Sun, Min-Chen Chen, Hui Nien Hung, Vincent S. Tseng
arXiv:2608.22899v1 Announce Type: new
Abstract: Unlike static medical question answering, long-horizon diagnosis captures the sequential nature of clinical practice: evidence is progressively acquire...
By Xiwei Dai, Zijie Meng, Zhiting Fan, Yixuan Tang, Ziru Niu, Zuozhu Liu
arXiv:2601. 03321v3 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have substantially advanced Radiology Report Generation (RRG), yet aligning them through reinforcement learning (RL) remains challenging due to heterogeneous medical supervision.
By Kun Zhao, Guodong Liu, Hui Ji, Siyuan Dai, Pan Wang, Jifeng Song, Chenghua Lin, Liang Zhan, Haoteng Tang
MedPAO‑VL is a multimodal agent that generates structured radiology reports from chest X‑rays using an explainable plan‑act‑observe loop. The system first interprets the image with a vision module that captures diagnostic uncertainty, then iteratively refines the report by correcting semantic discrepancies to better match visual findings. Evaluation shows improved clinical correctness and structural compliance, with expert ratings of 3.5/5 for accuracy and 4.3/5 for structure.
By Shrish Shrinath Vaidya, Gowthamaan Palani, Minmini Selvam, Gokulraja Srinivasaraja, Ganapathy Krishnamurthi
arXiv:2603. 01131v3 Announce Type: replace-cross Abstract: Clinical diagnosis is a gradual process of evidence integration, in which physicians move from symptoms and medical history to examinations, competing hypotheses, disease relations, and treatment decisions.
By Yuqi Zhan, Xinyue Wu, Tianyu Lin, Yutong Bao, Xiaoyu Wang, Weihao Cheng, Huangwei Chen, Feiwei Qin, Zhu Zhu