Improving Medical Diagnostics with Vision-Language Models: Convex Hull-Based Uncertainty Analysis [0.03%]
基于凸包的不确定性分析：用于改进医学诊断的视觉语言模型
Ferhat Ozgur Catak,Murat Kuzlu,Taylor Patrick et al.
Ferhat Ozgur Catak et al.
In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertain...
A Thyroid Nodule Differentiation Model for Benign-Malignant Identification by Fusing Transfer Learning and Gradient Boosting Decision Tree [0.03%]
基于迁移学习和梯度提升决策树融合的甲状腺结节良恶性鉴别模型
Bo Li,Tingxue Li,Hao Ju et al.
Bo Li et al.
Accurate identification of benign and malignant thyroid nodules is a core link in clinical diagnosis and treatment decision-making, which directly affects the selection of subsequent treatment plans for patients. Aiming at the problems such...
A Bounded Public DICOM Metadata Audit for UDI-DICOM Evidence Readiness in Medical Imaging Workflows [0.03%]
面向医疗成像工作流中UDI-DICOM证据准备性的有界公共DICOM元数据审计
Bin Zhang
Bin Zhang
The objective of this study is to assess whether selected public Digital Imaging and Communications in Medicine (DICOM) archive series contain archive-observable equipment-identity and Unique Device Identification (UDI)-related metadata nee...
Automated Body Composition from Computed Tomography Scans Improves Survival Prediction in Colorectal Cancer Patients [0.03%]
基于计算机断层扫描的自动化身体组成可改善结直肠癌患者的生存预测能力
Mushfiqus Salehin,Hyunwoo Lee,Vincent Tze Yang Chow et al.
Mushfiqus Salehin et al.
Colorectal cancer is one of the most common cancers, but the current staging system is limited by the variability and paradoxical survival outcomes. Body composition is an accurate predictor of survival and can be extracted from routine com...
Reliability-Aware View-Adaptive Consensus for 3D Cephalometric Landmark Identification [0.03%]
面向3D头影标志点识别的鲁棒自适应一致性方法
Min-Hyuk Choi,Jo-Eun Kim,Kyung-Hoe Huh et al.
Min-Hyuk Choi et al.
Cone-beam computed tomography (CBCT)-based three-dimensional (3D) cephalometric analysis relies on accurate anatomical landmark identification, yet manual annotation is time-consuming and subject to inter- and intra-observer variability. Wh...
Evaluating Clinical NLP Services for Chest Radiograph Report Labeling: A Comparative Study on an Independent Pediatric Dataset [0.03%]
基于独立儿科数据集的临床NLP服务评价：以胸部放射报告标注为例比较研究
Shruti Hegde,Mabon Manoj Ninan,Jonathan R Dillman et al.
Shruti Hegde et al.
General-purpose clinical NLP tools are increasingly used to automatically label clinical reports for research and quality improvement. However, independent evaluations for specific tasks like labeling pediatric CXR reports remain limited. T...
Automatic Grading of Age-Related Cataract via Progressive Ordinal Attention and Topology-Constrained Prototype Learning [0.03%]
基于渐进式序数注意力和拓扑约束原型学习的自动白内障分级系统
Zexin Xu,Cheng Wan,Xinya Hu et al.
Zexin Xu et al.
Age-related cataract is a leading cause of visual impairment among older adults, significantly affecting quality of life and independence. Accurate severity grading is essential for determining optimal surgical timing and improving clinical...
CMB-Net: A Clinically Modulated Boundary-Aware Network for Anatomical Segmentation of the Cervical Transformation Zone in Colposcopy [0.03%]
一种针对宫颈转化带解剖结构分割的临床调节边界感知网络(CMB-Net)
Ling Yan,Jiali Wu,Yi Guo et al.
Ling Yan et al.
Colposcopy is an essential tool for cervical precancer evaluation and biopsy guidance. Most existing artificial intelligence (AI) tools for cervicogram analysis are lesion-centric or limited to global transformation zone (TZ) classification...
Advancing the FAIRness of Multimodal Imaging Research Through the OMOP MI-CDM Framework: A Case Replication Study in Alzheimer's Disease [0.03%]
利用OMOP MI-CDM框架推进多模态影像学研究的FAIR性：阿尔茨海默病中的案例复制研究
Gabriel L O Salvador,Jen Wooyeon Park,Teri Sippel Schmidt et al.
Gabriel L O Salvador et al.
The objective of this study is to demonstrate an end-to-end approach for operationalizing the Findable, Accessible, Interoperable, and Reusable (FAIR) principles in multimodal medical imaging research using standardized data models and repr...
Explainable AI-Assisted Multimodal Ultrasound Radiomics for Preoperative Risk Stratification of Central Lymph Node Metastasis in Papillary Thyroid Carcinoma [0.03%]
基于可解释人工智能的多模态超声影像组学在乳头状甲状腺癌中央区淋巴结转移术前分层中的应用
Zhengqin Huang,Junjie Wang,Meiwen Chen et al.
Zhengqin Huang et al.
The objective was to develop and validate an explainable artificial intelligence (AI)-based multimodal approach for preoperative risk stratification of central lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC) and to evaluat...