医学 AI

Spitzoid Lesions Diagnosis based on GA feature selection and Random Forest

Abir Belaala, Labib Sadek, Noureddine Zerhouni, Christine Devalland

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、q-bio

CeliacNet: Celiac Disease Severity Diagnosis on Duodenal Histopathological Images Using Deep Residual Networks

Rasoul Sali, Lubaina Ehsan, Kamran Kowsari, Marium Khan, Christopher A. Moskaluk, Sana Syed, Donald E. Brown

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、q-bio

Comments accepted at IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2019)

Google Auto ML versus Apple Create ML for Histopathologic Cancer Diagnosis; Which Algorithms Are Better?

Andrew A. Borkowski, Catherine P. Wilson, Steven A. Borkowski, L. Brannon Thomas, Lauren A. Deland, Stefanie J. Grewe, Stephen M. Mastorides

专题命中 诊断辅助 ：diagnosis(title,abstract)；pathology(abstract)；分类 q-bio

Comments 18 pages, 1 table, 4 figures

How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis

Maria J. M. Chuquicusma, Sarfaraz Hussein, Jeremy Burt, Ulas Bagci

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、q-bio；biomedical(comments)

Comments Accepted for publication in IEEE International Symposium on Biomedical Imaging (ISBI) 2018

Position: Medical AI Neglects Real Treatment Outcomes

立场：医学人工智能忽视真实治疗结局

Shiva Kaul, Anjum Khurshid

专题命中 诊断辅助 ：medical AI(title,abstract)；biomedical(abstract)

AI总结 本论文指出医学AI忽视真实治疗结局，当前依赖文本而非真实数据，导致模型与基准存在缺陷，提出应将真实治疗结局纳入训练评估，并将优化其作为医学AI的下游目标。

Comments Published at ICML 2026. https://openreview.net/forum?id=0e1KEGU9RD

Uncertainty Reasoning with Large Language Models for Explainable Disease Diagnosis

基于大语言模型的不确定性推理用于可解释疾病诊断

Xiaoyang Fan, Yufan Cai, Zhe Hou, Jin Song Dong

机构 * National University of Singapore（新加坡国立大学） ； Griffith University（格里菲斯大学） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；medical AI(abstract)

AI总结 提出一种神经符号推理框架，将大语言模型与模糊逻辑和声明式规则结合，实现可解释且形式可验证的医学诊断。

Unsupervised Machine Learning for Osteoporosis Diagnosis Using Singh Index Clustering on Hip Radiographs

基于Singh指数聚类的髋部X光片中无监督机器学习用于骨质疏松症诊断

Vijaya Kalavakonda, Vimaladevi Madhivanan, Abhay Lal, Senthil Rithika, Shamala Karupusamy Subramaniam, Mohamed Sameer

机构 * Department of Computing Technologies, School of Computing, SRM Institute of Science and Technology（计算机技术系，计算学院，SRM科学与技术学院） ； Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia（通信技术与网络系，计算机科学与信息技术学院，马来西亚国立大学） ； Department of Orthopaedics, Sri Ramachandra Medical College（骨科系，Sri Ramachandra医学院） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 本文研究利用无监督机器学习自动识别髋部X光片中的Singh指数，通过改进的卷积神经网络提升聚类性能，探讨数据不平衡和图像质量对诊断的影响，提出结合临床数据和半监督学习的方法以提高准确性。

Deep Hierarchical Knowledge Loss for Fault Intensity Diagnosis

深度层次知识损失用于故障强度诊断

Yu Sha, Shuiping Gou, Bo Liu, Haofan Lu, Ningtao Liu, Jiahui Fu, Horst Stoecker, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou

机构 * School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）科学与工程学院） ； School of Artificial Intelligence, The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）人工智能学院） ； School of Artificial Intelligence, Xidian University（西安电子科技大学人工智能学院） ； School of Computer, Luoyang Institute of Science and Technology（洛阳理工学院计算机学院） ； Frankfurt Institute for Advanced Studies（法兰克福先进研究 institute） ； SAMSON AG（SAMSON公司） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.SP

AI总结 本文提出深度层次知识损失框架，通过层次树损失和焦点层次树损失提升故障诊断的识别能力，实验表明在多个工业数据集上优于现有方法。

Comments The paper has been accepted by Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1 (KDD 2026)

A Generalized Additive Partial-Mastery Cognitive Diagnosis Model

一种广义的加性部分掌握认知诊断模型

Camilo Cárdenas-Hurtado, Sze Ming Lee, Yunxiao Chen, Irini Moustaki

专题命中 诊断辅助 ：diagnosis(title,abstract)；biomedical(abstract)

AI总结 本文提出广义加性部分掌握认知诊断模型，通过非参数单调函数混合来放松传统模型的参数假设，提升模型适应性和解释性。

Comments 29 pages, 4 figures. Includes online appendix

MedRoute: RL-Based Dynamic Specialist Routing in Multi-Agent Medical Diagnosis

MedRoute: 基于强化学习的多智能体医疗诊断动态专家路由

Ashmal Vayani, Parth Parag Kulkarni, Joseph Fioresi, Song Wang, Mubarak Shah

机构 * Institute of Artificial Intelligence, University of Central Florida, Orlando, United States（中佛罗里达大学人工智能研究所，奥兰多，美国） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 本文提出MedRoute框架，通过强化学习动态选择专家进行医疗诊断，提升诊断准确性，优于现有基线方法。

EvoClinician: A Self-Evolving Agent for Multi-Turn Medical Diagnosis via Test-Time Evolutionary Learning

EvoClinician: 一种通过测试时进化学习进行多轮医学诊断的自进化代理

Yufei He, Juncheng Liu, Zhiyuan Hu, Yulin Chen, Yue Liu, Yuan Sui, Yibo Li, Nuo Chen, Jun Hu, Bryan Hooi, Xinxing Xu, Jiang Bian

机构 * Microsoft Research（微软研究院） ； National University of Singapore（新加坡国立大学） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；medical AI(abstract)

AI总结 EvoClinician通过测试时进化学习实现多轮医学诊断，采用'诊断-评分-进化'循环提升诊断效率

Mapis: A Knowledge-Graph Grounded Multi-Agent Framework for Evidence-Based PCOS Diagnosis

Mapis：一种基于知识图谱的多智能体框架，用于基于证据的多囊卵巢综合征诊断

Zanxiang He, Meng Li, Liyun Shi, Weiye Daia, Liming Nie

专题命中 诊断辅助 ：diagnosis(title,abstract)；radiology(abstract)

AI总结 Mapis是一种基于知识图谱的多智能体框架，专门用于基于指南的多囊卵巢综合征诊断，通过结构化协作流程和全面的知识图谱提升诊断准确性。

Alleviating Hyperparameter-Tuning Burden in SVM Classifiers for Pulmonary Nodules Diagnosis with Multi-Task Bayesian Optimization

Wenhao Chi, Haiping Liu, Hongqiao Dong, Wenhua Liang, Bo Liu

机构 * Yau Mathematical Sciences Center Tsinghua University（姚数学科学中心清华大学） ； The First Affiliated Hospital of Guangzhou Medical University（广州医科大学第一附属医院） ； China State Key Laboratory of Respiratory Disease（中国呼吸疾病国家重点实验室） ； Academy of Mathematics and Systems Science Chinese Academy of Sciences（数学科学学院中国科学院） ； University of Chinese Academy of Sciences（中国科学院大学） ； Department of Thoracic Surgery and Oncology The First Affiliated Hospital of Guangzhou Medical University（胸外科与肿瘤科广州医科大学第一附属医院） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Comments 12 pages, 4 figures, 37 references

AI-powered skin spectral imaging enables instant sepsis diagnosis and outcome prediction in critically ill patients

Silvia Seidlitz, Katharina Hölzl, Ayca von Garrel, Jan Sellner, Stephan Katzenschlager, Tobias Hölle, Dania Fischer, Maik von der Forst, Felix C. F. Schmitt, Alexander Studier-Fischer, Markus A. Weigand, Lena Maier-Hein, Maximilian Dietrich

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Comments Markus A. Weigand, Lena Maier-Hein and Maximilian Dietrich contributed equally

Journal ref Sci. Adv. 11, eadw1968 (2025)

How to Evaluate Medical AI

Ilia Kopanichuk, Petr Anokhin, Vladimir Shaposhnikov, Vladimir Makharev, Ekaterina Tsapieva, Iaroslav Bespalov, Dmitry V. Dylov, Ivan Oseledets

机构 * AIRI ； Moscow Institute of Physics and Technology（莫斯科物理技术学院） ； Skokovo Institute of Science and Technology（斯科克沃科学与技术研究所） ； Innopolis University（因诺普里斯大学） ； SberHealth ； Lomonosov Moscow State University（罗蒙诺索夫莫斯科国立大学） 纠错

专题命中 诊断辅助 ：medical AI(title,abstract)；diagnosis(abstract)

Comments 10 pages, 7 fugures

EndoFinder: Online Lesion Retrieval for Explainable Colorectal Polyp Diagnosis Leveraging Latent Scene Representations

Ruijie Yang, Yan Zhu, Peiyao Fu, Yizhe Zhang, Zhihua Wang, Quanlin Li, Pinghong Zhou, Xian Yang, Shuo Wang

专题命中 诊断辅助 ：diagnosis(title,abstract)；pathology(abstract)

UGGNet: Bridging U-Net and VGG for Advanced Breast Cancer Diagnosis

Tran Cao Minh, Nguyen Kim Quoc, Phan Cong Vinh, Dang Nhu Phu, Vuong Xuan Chi, Ha Minh Tan

机构 * School of Engineering, Tokyo Institute of Technology（东京技术大学工学院） ； Faculty of Information Technology Nguyen Tat Thanh University（Nguyen Tat Thanh大学信息科技学院） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Comments Submitted to the journal "EAI Endorsed Transactions on Context-aware Systems and Applications" ,2 images, 5 data tables

Journal ref EAI Endorsed Transactions on Contex-aware Systems and Applications, 10(1), 2024

Deep Transfer Learning for Kidney Cancer Diagnosis

Yassine Habchi, Hamza Kheddar, Yassine Himeur, Mohamed Chahine Ghanem, Abdelkrim Boukabou, Shadi Atalla, Wathiq Mansoor, Hussain Al-Ahmad

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Exploring Image Transforms derived from Eye Gaze Variables for Progressive Autism Diagnosis

Abigail Copiaco, Christian Ritz, Yassine Himeur, Valsamma Eapen, Ammar Albanna, Wathiq Mansoor

机构 * College of Engineering and Information Technology, University of Dubai, UAE（工程与信息技术学院，迪拜大学） ； School of Electrical, Computer, and Telecommunications Engineering, University of Wollongong, Australia（电气、计算机与电信工程学院，沃尔longong大学） ； College of Medicine and Health Sciences, Mohammed Bin Rashid University Dubai, UAE（医学与健康科学学院，迪拜穆罕默德·本·拉希德大学） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Comments 6 pages, 8 figures, and 1 table

MedOrch: Medical Diagnosis with Tool-Augmented Reasoning Agents for Flexible Extensibility

Yexiao He, Ang Li, Boyi Liu, Zhewei Yao, Yuxiong He

专题命中 诊断辅助 ：diagnosis(title,abstract)；healthcare AI(abstract)

Comparisons between a Large Language Model-based Real-Time Compound Diagnostic Medical AI Interface and Physicians for Common Internal Medicine Cases using Simulated Patients

Hyungjun Park, Chang-Yun Woo, Seungjo Lim, Seunghwan Lim, Keunho Kwak, Ju Young Jeong, Chong Hyun Suh

专题命中 诊断辅助 ：medical AI(title,abstract)；diagnosis(abstract)

A portable diagnosis model for Keratoconus using a smartphone

Yifan Li, Peter Ho, Jo Woon Chong

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Proof-of-TBI -- Fine-Tuned Vision Language Model Consortium and OpenAI-o3 Reasoning LLM-Based Medical Diagnosis Support System for Mild Traumatic Brain Injury (TBI) Prediction

Ross Gore, Eranga Bandara, Sachin Shetty, Alberto E. Musto, Pratip Rana, Ambrosio Valencia-Romero, Christopher Rhea, Lobat Tayebi, Heather Richter, Atmaram Yarlagadda, Donna Edmonds, Steven Wallace, Donna Broshek

机构 * Old Dominion University（旧 Dominion 大学） ； McDonald Army Health Center（麦克唐纳陆军医疗中心） ； BRAINBox Solutions（BRAINBox 解决方案） ； UVA Health（弗吉尼亚大学健康系统） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；MRI(abstract)

An Explainable Nature-Inspired Framework for Monkeypox Diagnosis: Xception Features Combined with NGBoost and African Vultures Optimization Algorithm

Ahmadreza Shateri, Negar Nourani, Morteza Dorrigiv, Hamid Nasiri

机构 * Electrical and Computer Engineering Department, Semnan University, Semnan, Iran（塞姆南大学电气与计算机工程系） ； School of Computing and Communications, Lancaster University, Lancaster, UK（兰卡斯特大学计算与通信学院） 纠错

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Deep Learning-Based Automatic Diagnosis System for Developmental Dysplasia of the Hip

Yang Li, Leo Yan Li-Han, Hua Tian

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

HIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic Diagnosis

Haoxu Huang, Cem M. Deniz, Kyunghyun Cho, Sumit Chopra, Divyam Madaan

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Comments In Proceedings of Machine Learning for Health

Journal ref PMLR 259(2025):502-523

Explainable AI for Autism Diagnosis: Identifying Critical Brain Regions Using fMRI Data

Suryansh Vidya, Kush Gupta, Amir Aly, Andy Wills, Emmanuel Ifeachor, Rohit Shankar

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Comments This work has been submitted to the IEEE for possible publication

An Integrated Deep Learning Framework Leveraging NASNet and Vision Transformer with MixProcessing for Accurate and Precise Diagnosis of Lung Diseases

Sajjad Saleem, Muhammad Imran Sharif

专题命中 诊断辅助 ：diagnosis(title)；medical image(abstract)；分类 cs.CV、cs.LG、eess.IV

Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study

Yanjun Gao, Ruizhe Li, Emma Croxford, John Caskey, Brian W Patterson, Matthew Churpek, Timothy Miller, Dmitriy Dligach, Majid Afshar

专题命中 诊断辅助 ：diagnosis(title,abstract)；biomedical(abstract)

Comments Published in JMIR AI

Deeply Supervised Skin Lesions Diagnosis with Stage and Branch Attention

Wei Dai, Rui Liu, Tianyi Wu, Min Wang, Jianqin Yin, Jun Liu

专题命中 诊断辅助 ：diagnosis(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Comments 11 pages, 9 figures