医学 AI

Ontology Enrichment from Texts: A Biomedical Dataset for Concept Discovery and Placement

Hang Dong, Jiaoyan Chen, Yuan He, Ian Horrocks

专题命中 医学数据与评测 ：biomedical(title)；CT(abstract)

Comments 5 pages, 1 figure, accepted for CIKM 2023. The dataset, data construction scripts, and baseline implementation are available at https://zenodo.org/record/8228005 (Zenodo) and https://github.com/KRR-Oxford/OET (GitHub)

MDDial: A Multi-turn Differential Diagnosis Dialogue Dataset with Reliability Evaluation

Srija Macherla, Man Luo, Mihir Parmar, Chitta Baral

专题命中 医学数据与评测 ：diagnosis(title,abstract)

Revisiting Automatic Question Summarization Evaluation in the Biomedical Domain

Hongyi Yuan, Yaoyun Zhang, Fei Huang, Songfang Huang

专题命中 医学数据与评测 ：biomedical(title,abstract)

Comments 8 pages, 1 figure

Context Variance Evaluation of Pretrained Language Models for Prompt-based Biomedical Knowledge Probing

Zonghai Yao, Yi Cao, Zhichao Yang, Hong Yu

专题命中 医学数据与评测 ：biomedical(title,abstract)

Comments Presented at the AMIA 2023 Informatics Summit as an oral paper

A Dataset for Plain Language Adaptation of Biomedical Abstracts

Kush Attal, Brian Ondov, Dina Demner-Fushman

专题命中 医学数据与评测 ：biomedical(title,abstract)

Comments 12 pages, 4 figures, 7 tables

Analysing the Influence of Attack Configurations on the Reconstruction of Medical Images in Federated Learning

Mads Emil Dahlgaard, Morten Wehlast Jørgensen, Niels Asp Fuglsang, Hiba Nassar

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV、cs.LG、eess.IV

Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods

William Paul, Yinzhi Cao, Miaomiao Zhang, Phil Burlina

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV、cs.LG、eess.IV

Comments Accepted for oral presentation at MICCAI PPML 2021

Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud

Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng

专题命中 医学数据与评测 ：diagnosis(title,abstract)

Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets

Yifan Peng, Shankai Yan, Zhiyong Lu

专题命中 医学数据与评测 ：biomedical(title,abstract)

Comments Accepted by BioNLP 2019

MedCTA: A Benchmark for Clinical Tool Agents

MedCTA: 临床工具智能体基准

Tajamul Ashraf, Hyewon Jeong, Fida Mohammad Thoker, Bernard Ghanem

机构 * King Abdullah University of Science and Technology (KAUST)（阿卜杜拉国王科技大学） ； Massachusetts Institute of Technology (MIT)（麻省理工学院） 纠错

专题命中 医学数据与评测 ：medical AI(abstract)；pathology(abstract)；radiology(abstract)；分类 cs.CV

AI总结 提出MedCTA基准，基于放射影像、病理切片和报告等真实临床多模态输入，评估医疗AI智能体在工具检索、证据获取和集成方面的规划与执行能力。

Comments Project Page: https://ivul-kaust.github.io/MedCTA/ Code: https://github.com/IVUL-KAUST/MedCTA Data: https://huggingface.co/datasets/IVUL-KAUST/MedCTA

Zero-Shot Generative De-identification: Inversion-Free Flow for Privacy-Preserving Skin Image Analysis

零样本生成去标识化：无反向流程的隐私保护皮肤图像分析

Konstantinos Moutselos, Ilias Maglogiannis

机构 * University of Piraeus, Dept. of Digital Systems（比雷埃夫斯大学数字系统系） 纠错

专题命中 医学数据与评测 ：medical image(abstract)；pathology(abstract)；biomedical(abstract)；分类 cs.CV

AI总结 本文提出一种零样本生成去标识化框架，利用无反向流程实现隐私保护的医学图像分析，通过Rectified Flow Transformers在20秒内实现高保真身份转换，无需病理特定训练或标注数据，生成虚拟健康与病理对照对以分离临床信号。

Comments 10 pages, 5 figures

Med-MMFL: A Multimodal Federated Learning Benchmark in Healthcare

Med-MMFL：医疗领域的多模态联邦学习基准

Aavash Chhetri, Bibek Niroula, Pratik Shrestha, Yash Raj Shrestha, Lesley A Anderson, Prashnna K Gyawali, Loris Bazzani, Binod Bhattarai

机构 * University of Aberdeen（阿伯丁大学） ； NepAl Applied Mathematics and Informatics Institute for research, Nepal（尼泊尔应用数学与信息学研究所） ； University of Lausanne（洛桑大学） ； West Virginia University（西弗吉尼亚大学） ； University of Verona（威尼斯大学） ； University College London（伦敦大学学院） 纠错

专题命中 医学数据与评测 ：MRI(abstract)；pathology(abstract)；radiology(abstract)；分类 cs.CV

AI总结 Med-MMFL是首个医疗领域多模态联邦学习基准，涵盖多种模态和任务，评估六种先进算法以推动医疗多模态联邦学习的研究。

MeniMV: A Multi-view Benchmark for Meniscus Injury Severity Grading

MeniMV：一种多视图的半月板损伤严重程度分级基准

Shurui Xu, Siqi Yang, Jiapin Ren, Zhong Cao, Hongwei Yang, Mengzhen Fan, Yuyu Sun, Shuyan Li

机构 * Queen's University Belfast（女王大学贝尔法斯特分校） ； Nantong University（南通大学） ； China University of Mining and Technology（中国矿业大学） ； Heidelberg University（海德堡大学） ； Peking University（北京大学） 纠错

专题命中 医学数据与评测 ：MRI(abstract)；pathology(abstract)；diagnosis(abstract)；分类 cs.CV

AI总结 MeniMV是一种多视图基准数据集，用于半月板horn损伤严重程度分级，通过提供丰富的标注数据和双视图诊断上下文，推动自动化MRI分析的发展。

Comments 5 pages, 2 figures

Federated Learning for Large Models in Medical Imaging: A Comprehensive Review

Mengyu Sun, Ziyuan Yang, Yongqiang Huang, Hui Yu, Yingyu Chen, Shuren Qi, Andrew Beng Jin Teoh, Yi Zhang

机构 * School of Cyber Science and Engineering, Sichuan University（四川大学网络科学与工程学院） ； Sichuan Institute of Computer Sciences（四川省计算机科学研究院） ； College of Computer Science, Sichuan University（四川大学计算机学院） ； Department of Mathematics, The Chinese University of Hong Kong（香港中文大学数学系） ； School of Electrical and Electronic Engineering, College of Engineering, Yonsei University（延世大学工程学院电子与电气工程系） 纠错

专题命中 医学数据与评测 ：MRI(abstract)；CT(abstract)；diagnosis(abstract)；分类 cs.CV

FedDP: Privacy-preserving method based on federated learning for histopathology image segmentation

Liangrui Pan, Mao Huang, Lian Wang, Pinle Qin, Shaoliang Peng

专题命中 医学数据与评测 ：medical image(abstract)；pathology(abstract)；diagnosis(abstract)；分类 cs.CV

Comments Accepted in BIBM2024

Exploring the Effect of Dataset Diversity in Self-Supervised Learning for Surgical Computer Vision

Tim J. M. Jaspers, Ronald L. P. D. de Jong, Yasmina Al Khalil, Tijn Zeelenberg, Carolus H. J. Kusters, Yiping Li, Romy C. van Jaarsveld, Franciscus H. A. Bakker, Jelle P. Ruurda, Willem M. Brinkman, Peter H. N. De With, Fons van der Sommen

专题命中 医学数据与评测 ：medical image(abstract)；pathology(abstract)；radiology(abstract)；分类 cs.CV

Comments accepted - Data Engineering in Medical Imaging (DEMI) Workshop @ MICCAI2024

Journal ref Data Engineering in Medical Imaging. DEMI 2024. Lecture Notes in Computer Science

Image-aware Evaluation of Generated Medical Reports

Gefen Dawidowicz, Elad Hirsch, Ayellet Tal

专题命中 医学数据与评测 ：pathology(abstract)；diagnosis(abstract)；radiology(abstract)；分类 cs.CV

Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation

Shen Wang, Kongming Liang, Yiming Li, Yizhou Yu, Yizhou Wang

专题命中 医学数据与评测 ：CT(abstract)；pathology(abstract)；diagnosis(abstract)；分类 cs.CV

UniToBrain dataset: a Brain Perfusion Dataset

Daniele Perlo, Enzo Tartaglione, Umberto Gava, Federico D'Agata, Edwin Benninck, Mauro Bergui

专题命中 医学数据与评测 ：CT(abstract)；diagnosis(abstract)；分类 cs.CV、cs.LG、eess.IV；biomedical(comments)

Comments Workshop ICIAP 2021 - Deep-Learning and High Performance Computing to Boost Biomedical Applications

Virtual vs. Reality: External Validation of COVID-19 Classifiers using XCAT Phantoms for Chest Computed Tomography

Fakrul Islam Tushar, Ehsan Abadi, Saman Sotoudeh-Paima, Rafael B. Fricks, Maciej A. Mazurowski, W. Paul Segars, Ehsan Samei, Joseph Y. Lo

专题命中 医学数据与评测 ：diagnosis(abstract,comments)；CT(abstract)；分类 cs.CV、cs.LG、eess.IV

Comments 7 pages, 5 figures, 2 tables, presented at the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

Evaluation of Big Data based CNN Models in Classification of Skin Lesions with Melanoma

Prasitthichai Naronglerdrit, Iosif Mporas

专题命中 医学数据与评测 ：diagnosis(abstract,comments)；pathology(abstract)；分类 cs.CV、cs.LG、eess.IV

Comments Series Title: Studies in Computational Intelligence, Book Title: Deep Learning for Cancer Diagnosis, Series Volume: 908, DOI: 10.1007/978-981-15-6321-8, eBook ISBN: 978-981-15-6321-8

The pretraining domain outweighs the training objective in setting the privacy-utility trade-off of differentially private medical image analysis

自监督预训练在差分隐私医疗图像分析中的作用

Soroosh Tayebi Arasteh, Mina Farajiamiri, Mahshad Lotfinia, Behrus Hinrichs-Puladi, Jonas Bienzeisler, Mohamed Alhaskir, Mirabela Rusu, Christiane Kuhl, Sven Nebelung, Daniel Truhn

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV、cs.LG

AI总结 本文研究了自监督预训练在差分隐私医疗图像分析中的作用，发现DINOv3初始化在DP下优于ImageNet初始化，但不如领域特定监督预训练。

MODE-RAG: Manifold Outlier Diagnosis and Energy-based Retrieval-Augmented Generation Evaluation

MODE-RAG: 基于流形异常诊断和能量的检索增强生成评估

Zehang Wei, Jiaxin Dai, Jiamin Yan, Xiang Xiang

机构 * School of Computer Science & Tech, Huazhong University of Science and Technology（华中科技大学计算机科学与技术学院） ； School of AI and Automation, Huazhong University of Science and Technology（华中科技大学人工智能与自动化学院） 纠错

专题命中 医学数据与评测 ：diagnosis(title)；分类 cs.CV、cs.LG

AI总结 提出MODE-RAG多智能体系统，利用变分自由能和内部注意力状态动态门控干预，结合蒙特卡洛树搜索和logit扰动减少多模态检索增强生成中的幻觉和逻辑捏造。

Comments To be presented at ACL 2026

DermaCon-IN: A Multi-concept Annotated Dermatological Image Dataset of Indian Skin Disorders for Clinical AI Research

DermaCon-IN：一个包含印度皮肤疾病多概念标注的皮肤病图像数据集，用于临床AI研究

Shanawaj S Madarkar, Mahajabeen Madarkar, Madhumitha Venkatesh, Deepanshu Bansal, Teli Prakash, Konda Reddy Mopuri, Vinaykumar MV, KVL Sathwika, Adarsh Kasturi, Gandla Dilip Raj, PVN Supranitha, Harsh Udai

机构 * Department of Artificial Intelligence, Indian Institute of Technology Hyderabad, India（人工智能系，印度理工学院海得拉巴学院，印度） ； Indian Navy（印度海军） ； Department of Dermatology, S R Patil Medical College, India（皮肤科系，S R Patil医学院，印度） ； Department of Dermatology, S Nijalingappa Medical College, India（皮肤科系，S Nijalingappa医学院，印度） ； Department of Dermatology, Sri Chamundeshwari Medical College, Hospital & Research, India（皮肤科系，Sri Chamundeshwari医学院，医院及研究，印度） ； Indian Institute of Technology Hyderabad, India（印度理工学院海得拉巴学院，印度） 纠错

专题命中 医学数据与评测 ：clinical AI(title)；分类 cs.CV、eess.IV

AI总结 DermaCon-IN是一个包含印度皮肤疾病多概念标注的皮肤病图像数据集，用于临床AI研究，旨在提供可扩展且具有代表性的基础，推动皮肤病AI的发展。

Comments Accepted at NeurIPS 2025 (D&B Track)

RRTS Dataset: A Benchmark Colonoscopy Dataset from Resource-Limited Settings for Computer-Aided Diagnosis Research

Ridoy Chandra Shil, Ragib Abid, Tasnia Binte Mamun, Samiul Based Shuvo, Masfique Ahmed Bhuiyan, Jahid Ferdous

机构 * Department of Biomedical Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh（生物医学工程系，孟加拉国工程大学） ； Dhaka Medical College, Dhaka, Bangladesh（达卡医学学院） 纠错

专题命中 医学数据与评测 ：diagnosis(title)；分类 cs.CV、eess.IV

Accurate and Private Diagnosis of Rare Genetic Syndromes from Facial Images with Federated Deep Learning

Ali Burak Ünal, Cem Ata Baykara, Peter Krawitz, Mete Akgün

机构 * Medical Data Privacy and Privacy Preserving Machine Learning (MDPPML)（医学数据隐私与隐私保护机器学习） ； University of Tübingen（图宾根大学） ； Institute for Bioinformatics and Medical Informatics (IBMI)（生物信息学与医学信息学研究所） ； Institute for Genomic Statistics and Bioinformatics（基因组统计与生物信息学研究所） ； University of Bonn（波恩大学） 纠错

专题命中 医学数据与评测 ：diagnosis(title)；分类 cs.CV、cs.LG

Evaluation of 3D Counterfactual Brain MRI Generation

Pengwei Sun, Wei Peng, Lun Yu Li, Yixin Wang, Kilian M. Pohl

机构 * Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA Department of Radiology, Stanford University, Stanford, CA, USA Dept. of Psychiatry \& Behavioral Sciences, Stanford University, Stanford, CA, USA Department of Computer Science, Stanford University, Stanford, CA, USA Department of Bioengineering, Stanford University, Stanford, CA, USA Department of Electrical Engineering, Stanford University, Stanford, CA, USA 纠错

专题命中 医学数据与评测 ：MRI(title)；分类 cs.CV、eess.IV

Detecting Dataset Bias in Medical AI: A Generalized and Modality-Agnostic Auditing Framework

Nathan Drenkow, Mitchell Pavlak, Keith Harrigian, Ayah Zirikly, Adarsh Subbaswamy, Mohammad Mehdi Farhangi, Nicholas Petrick, Mathias Unberath

机构 * The Johns Hopkins University（约翰霍普金斯大学） ； The Johns Hopkins University Applied Physics Laboratory（约翰霍普金斯大学应用物理实验室） ； Center for Devices and Radiological Health, U.S. Food and Drug Administration（美国食品药品监督管理局设备与放射健康中心） 纠错

专题命中 医学数据与评测 ：medical AI(title)；分类 cs.CV、cs.LG

Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering

He Zhu, Ren Togo, Takahiro Ogawa, Miki Haseyama

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV、cs.LG

Lab-scale Vibration Analysis Dataset and Baseline Methods for Machinery Fault Diagnosis with Machine Learning

Bagus Tris Atmaja, Haris Ihsannur, Suyanto, Dhany Arifianto

专题命中 医学数据与评测 ：diagnosis(title)；分类 cs.LG、eess.SP