科学与医疗

医学 AI

医学智能、临床 AI、医学影像、病理、诊断和医疗健康大模型。

2026-01-12 至 2026-01-12 共收录 2 篇信号源：cs.CV, cs.LG, q-bio, eess.IV, eess.SP

1. 诊断辅助 2 篇

2601.05373 2026-01-12 cs.CV cs.AI 79%

Ensemble of radiomics and ConvNeXt for breast cancer diagnosis

放射组学与ConvNeXt的集成用于乳腺癌诊断

Jorge Alberto Garza-Abdala, Gerardo Alejandro Fumagal-González, Beatriz A. Bosques-Palomo, Mario Alexis Monsivais Molina, Daly Avedano, Servando Cardona-Huerta, José Gerardo Tamez-Pena

机构 * School of Science and Engineering（科学与工程学院）； Tecnologico de Monterrey（蒙特雷理工大学）； School of Medicine and Health Sciences（医学与健康科学学院）

专题命中诊断辅助：diagnosis(title,abstract)；分类 cs.CV

AI总结本文提出利用放射组学与ConvNeXt的集成方法，提升乳腺癌乳腺X线片的诊断性能，实现更高的AUC值。

Comments Accepted and presented at the IEEE International Symposium on Computer-Based Medical Systems (CBMS) 2025

Journal ref 2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS)

2211.15664 2026-01-12 cs.LG cs.CE 57%

Utilising physics-guided deep learning to overcome data scarcity

利用物理引导的深度学习克服数据稀缺

Jinshuai Bai, Laith Alzubaidi, Qingxia Wang, Ellen Kuhl, Mohammed Bennamoun, Yuantong Gu

专题命中诊断辅助：diagnosis(abstract)；分类 cs.LG

AI总结本文提出利用物理引导的深度学习方法，在数据稀缺情况下提升模型的准确性和泛化能力，并探讨其在多个领域的应用与未来发展方向。

Comments This submission has been withdrawn because the manuscript is a review-type work that has become substantially out of date. Further assessment indicated that several sections were incomplete and did not adequately reflect the current state of the literature. The authors therefore plan to develop a new manuscript and may submit it elsewhere