Pai 的 AI 雷达

生信医疗

今天:Large language models(arXiv:2610),An AI-Based Multi-Stage(arXiv:2610)。并行还有 Answering clinicians、Bridging Research and、CRAFT。

日期
2026/10/06
今日条目
80
当前类目
5
#01

Large language models exhibit unreliable updating of clinical judgment as patient evidence evolves

arXiv:2610.02684v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored for clinical reasoning, but whether they appropriately revise judgments as patient evidence evolves remains unclear. We evaluated longitudinal belief updating using matched inte

推荐理由Large language models exhibit:arXiv:2610.02684v1 Announce Type: new Abstract: Large language models (LLMs) are。
模型与评测生信医疗arXiv cs.AI 官方
#02

An AI-Based Multi-Stage Approach for Androgenetic Alopecia Assessment from Low-Magnification Scalp Images

arXiv:2610.02421v1 Announce Type: new Abstract: Androgenetic alopecia (AGA) is characterized by patterned follicular miniaturization, increased single-hair follicular units, and altered hair-shaft diameter. We present an automated quantitative scalp-analysis and clinical decision

推荐理由An AI-Based Multi-Stage Approach:arXiv:2610.02421v1 Announce Type: new Abstract: Androgenetic alopecia (AGA) is。
模型与评测生信医疗arXiv cs.CV 官方
#03

Answering clinicians' questions over trial evidence tables with verifiable, feedback-driven language models

arXiv:2610.02576v1 Announce Type: new Abstract: Systematic reviews condense clinical trials into evidence tables, yet clinicians can interrogate these tables only through database queries, and many questions concern attributes that the table does not record, such as a drug's targ

推荐理由Answering clinicians' questions over:arXiv:2610.02576v1 Announce Type: new Abstract: Systematic reviews condense clinical。
模型与评测生信医疗arXiv cs.AI 官方
#04

Bridging Research and Practice: A Systematic Evaluation of Generalist and Dermatology-Specific Models in Clinical Skin Lesion Classification

arXiv:2610.03193v1 Announce Type: new Abstract: The application of machine learning to dermatology has grown substantially in recent years, moving beyond proof-of-concept studies toward potential applications. However, clinical dermatology remains a challenging and still open pro

推荐理由Bridging Research and Practice::arXiv:2610.03193v1 Announce Type: new Abstract: The application of machine learning。
模型与评测生信医疗arXiv cs.CV 官方
#05

CRAFT: Causal Responsibility and Failure Tracing in Medical Vision Language Models

arXiv:2609.38810v2 Announce Type: replace-cross Abstract: As vision language models are increasingly deployed in clinical diagnosis, under standing how they internally resolve competing visual and textual signals becomes a safety imperative. Existing mechanistic analyses remain c

推荐理由CRAFT: Causal Responsibility:arXiv:2609.38810v2 Announce Type: replace-cross Abstract: As vision language models are。
模型与评测生信医疗arXiv cs.AI 官方