Pai 的 AI 雷达

生信医疗

今天:A rubric landscape(arXiv:2610),Decision language models(arXiv:2610)。并行还有 An Evidence-Driven M、Arbitrary-Scale Anis、Beyond Masks and。

日期
2026/10/23
今日条目
95
当前类目
7
#01

A rubric landscape for evaluating clinical reasoning in large language models: what exists, what is missing, and what needs to be combined

arXiv:2610.01938v2 Announce Type: replace-cross Abstract: Exam-style accuracy does not establish whether large language models (LLMs) reason well over clinical records. We define clinical reasoning as integrating and updating evidence across time and sources to form, revise and j

推荐理由A rubric landscape for evaluating:arXiv:2610.01938v2 Announce Type: replace-cross Abstract: Exam-style accuracy does not。
模型与评测生信医疗arXiv cs.AI 官方
#02

Decision language models as affordable and rapid alternatives to LLM judges of clinical generative AI

arXiv:2610.28826v1 Announce Type: new Abstract: Automated judges of clinical artificial intelligence (AI) outputs are necessary, but large language model (LLM) judges are costly and slow at scale. We compared Jev, a decision language model that returns structured judgments, with

推荐理由Decision language models as affordable:arXiv:2610.28826v1 Announce Type: new Abstract: Automated judges of clinical artificial。
模型与评测生信医疗arXiv cs.AI 官方
#03

An Evidence-Driven Multi-Agent Compound AI System for Head and Neck Proton Radiotherapy Planning

arXiv:2610.29010v1 Announce Type: new Abstract: Radiation treatment planning requires balancing competing objectives to satisfy clinical criteria while accommodating physicians' preferences. This study aims to develop an evidence-driven, multi-agent compound AI system that integr

推荐理由An Evidence-Driven Multi-Agent Compound:arXiv:2610.29010v1 Announce Type: new Abstract: Radiation treatment planning requires。
模型与评测生信医疗arXiv cs.AI 官方
#04

Arbitrary-Scale Anisotropic 3D MRI Super-Resolution with Gaussian Prototypes

arXiv:2610.24858v2 Announce Type: replace Abstract: Reducing MRI acquisition time improves patient comfort, reduces motion artefacts, and increases scanner throughput. Clinical protocols often shorten acquisitions by sacrificing spatial resolution, particularly along the slice ax

推荐理由Arbitrary-Scale Anisotropic 3D MRI:arXiv:2610.24858v2 Announce Type: replace Abstract: Reducing MRI acquisition time。
模型与评测生信医疗arXiv cs.CV 官方
#05

Beyond Masks and Trajectories: Flow-Guided Latent Action Injection for Stable Surgical Video Generation

arXiv:2610.09800v2 Announce Type: replace Abstract: Surgical video generation holds substantial potential for surgical education, simulation, and data augmentation, yet generating surgical videos with realistic and clinically plausible motion remains challenging. Most existing me

推荐理由Beyond Masks and Trajectories:arXiv:2610.09800v2 Announce Type: replace Abstract: Surgical video generation holds。
模型与评测生信医疗arXiv cs.CV 官方
#06

Carving Radiology Reports at Their Evidential Joints: Anatomical Region Sets as Generation Units

arXiv:2610.29165v1 Announce Type: cross Abstract: Organizing radiology reports into independently generated units offers a way to generate fine-grained clinical content and bind it to visual evidence. However, existing methods typically adopt generation-unit structures not direct

推荐理由Carving Radiology Reports at Their:arXiv:2610.29165v1 Announce Type: cross Abstract: Organizing radiology reports into。
模型与评测生信医疗arXiv cs.CV 官方
#07

Clinical radar heart sounds with echocardiographic phenotypes of ventricular dysfunction and valvular disease

arXiv:2610.29267v1 Announce Type: new Abstract: Radar heart sounds capture cardiac mechanical activity without contact, while echocardiography characterizes ventricular and valvular function. Paired measurements connect these signals to structural heart disease, yet such data rem

推荐理由Clinical radar heart sounds:arXiv:2610.29267v1 Announce Type: new Abstract: Radar heart sounds capture cardiac。
模型与评测生信医疗arXiv cs.CV 官方