From Gram Stain to Decision Support: Performance of Multimodal Large Language Models in Blood Culture Microscopy [0.03%]
从革兰氏染色到决策支持：多模态大型语言模型在血液培养显微镜检查中的表现
Canset Nur Aydogan,Ilgaz Kazaz,Tuğrul Hoşbul
Canset Nur Aydogan
Multimodal large language models (LLMs) offer significant potential for image-based diagnostics, yet their reliability in routine clinical microbiology workflows, specifically Gram stain interpretation, remains insufficiently characterized....
SCA-Net: A Scale- and Contrast-Aware Network for Subtle and Low-Contrast Polyp Segmentation [0.03%]
SCA-Net：一种尺度感知和对比度感知网络用于细小低对比度息肉的分割
Jiaxu Huang,Yiyue Li,Jiaqi Zhang et al.
Jiaxu Huang et al.
Accurate polyp segmentation is critical for early detection of colorectal cancer. However, existing methods often struggle with subtle polyps, weak boundaries, and poor cross-dataset generalization. To address these challenges, we propose S...
Advanced Deep Learning Architectures in MRI-Based Brain Tumor Classification: A Systematic Review Focused on Meningiomas [0.03%]
基于MRI的脑肿瘤分类中 meningioma的系统性综述与深度学习架构的发展关系探究
Naima Noor,Clinton Turner,Samantha J Holdsworth et al.
Naima Noor et al.
Deep learning (DL) is increasingly applied to automate brain tumor classification from magnetic resonance imaging (MRI), yet meaningful clinical deployment remains limited by tumor heterogeneity, dataset bias, and incomplete tumor-specific ...
Non-invasive Multimodal Cardiovascular Disease Detection Method Based on Comprehensive View Analysis [0.03%]
基于综合视角分析的非侵入式心血管疾病多模态检测方法
Yining Xie,Kaiwen Zhang,Jun Long et al.
Yining Xie et al.
In recent years, researchers have found that the diagnosis of cardiovascular disease (CVD) is closely related to retinal fundus images and specific clinical indicators. However, current diagnostic methods are still limited to analyzing sing...
Deep Learning-Assisted Three-Dimensional Segmentation of Vertebrobasilar Artery Calcification in Cone Beam Computed Tomography [0.03%]
基于深度学习的椎基底动脉钙化锥形束CT三维分割
Kardelen Demirezer,Salih Taha Alperen Özçelik,Oğuzhan Altun et al.
Kardelen Demirezer et al.
VBAC assessment is crucial for stroke risk evaluation, but manual segmentation is time-consuming and subject to inter-observer variability. We developed a novel deep learning model specifically optimized for small vascular structure detecti...
Embedding Anisotropy in Medical Image Foundation Models: Post Hoc Whitening Degradation and Spectral-Aware Standardization [0.03%]
医学图像基础模型中的各向异性嵌入：事后白化退化和谱Aware标准化
Clemente García-Hidalgo
Clemente García-Hidalgo
Foundation models produce high-dimensional embedding representations whose geometric properties fundamentally determine downstream task effectiveness. Embedding anisotropy-the concentration of representations in a narrow cone-has been docum...
Opportunistic Promptable Segmentation: Leveraging Routine Radiological Annotations to Guide 3D CT Lesion Segmentation [0.03%]
Opportunctic提示式分割：利用常规放射学注释指导3D CT病变分割
Samuel Church,Joshua D Warner,Danyal Maqbool et al.
Samuel Church et al.
The development of machine learning models for CT imaging depends on the availability of large, high-quality, and diverse annotated datasets. Although large volumes of CT images and reports are readily available in clinical picture archivin...
Pritam Mandal,Swagata Kundu,Aatreya Sengupta et al.
Pritam Mandal et al.
Diabetic retinopathy (DR) is a serious eye condition caused by damage to the retina due to prolonged diabetes. Among the first signs of DR are microaneurysms and hemorrhages, collectively called red lesions. Detecting these lesions is cruci...
Radiologist Detection of Deficiencies in LLM-Generated Patient Communications About Radiology Reports: A Multi-Reader Study [0.03%]
放射科医师检测LLM生成的关于放射学报告的患者沟通中的缺陷的多读者研究
Cheong Shin,Jung Hyun Park,Sungjun Kim et al.
Cheong Shin et al.
Patients increasingly use large language models (LLMs) to interpret radiology reports, yet the reliability of radiologist oversight in detecting errors in patient-facing LLM responses remains unquantified. This study evaluated the diagnosti...
3D OCT-Based Retinal Biomarker Analysis for Automatic Regional-Wise Characterization of Neurodegenerative Diseases [0.03%]
基于3D OCT的视网膜生物标志物分析用于神经退行性疾病的自动区域性表征
Lorena Álvarez-Rodríguez,Carlota Vázquez,Beatriz Cordón et al.
Lorena Álvarez-Rodríguez et al.
Neurodegenerative diseases (NDDs) such as Alzheimer's disease (AD), essential tremor (ET), multiple sclerosis (MS), and Parkinson's disease (PD) are complex disorders that often exhibit overlapping symptoms, leading to diagnostic challenges...