Semi-supervised abdominal multi-organ segmentation via dual-task de-biased consistency [0.03%]
基于双重任务去偏一致性的时间序列半监督多器官分割方法
Lina Chen,Xinchi Ye,Yiqiu Tong et al.
Lina Chen et al.
Abdominal multi-organ segmentation suffers from the problems of unbalanced classes and difficult learning of dynamic organs, which leads to the segmentation effect being seriously affected. We present a dual-task de-bias consistency semi-su...
Disulfidptosis-associated gene signatures in sepsis: a diagnostic model based on an LLM-assisted bioinformatics analysis [0.03%]
基于LLM辅助生物信息学分析的脓毒症中与二硫连接素相关基因特征的诊断模型
Tian Liu,Zhi Mao,Jiake Chai et al.
Tian Liu et al.
Purpose: This study investigated the involvement of disulfidptosis in the pathophysiology of sepsis by applying a bioinformatics analysis assisted by large language models (LLMs). ...
Association between high-dose calcium supplementation during pregnancy and risk of placental disorders and low birth weight in Iranian women [0.03%]
钙补充剂与伊朗妇女的胎盘疾病和低体重出生儿风险之间的关系
Seyedeh Hajar Sharami,Sedigheh Hantoshzadeh,Forozan Milani et al.
Seyedeh Hajar Sharami et al.
Objective: Although calcium is crucial for maternal and fetal health, the association between high-dose calcium supplementation during pregnancy and adverse outcomes is not fully understood. This study examined the associ...
A hybrid deep learning approach for accurate diagnosis of tibiofibula open and closed fractures using x-ray images [0.03%]
基于X射线图像的胫腓骨开放性及闭合性骨折准确诊断的混合深度学习方法
Yapeng Wang,Peng Wang,Junhao Luo et al.
Yapeng Wang et al.
Background: Open fractures are critical injuries that require prompt and accurate diagnosis to optimize treatment outcomes. Traditional methods often rely on manual interpretation of radiological images, which can be pron...
Detecting self-harm in social media using term weighting schemes based on the distance between words and personal pronouns [0.03%]
基于词距和人称代词的术语加权方案在社交媒体自伤识别中的应用研究
Luz Maria Hernandez-Felipe,Rosa María Ortega-Mendoza,Fernando Sánchez-Vega et al.
Luz Maria Hernandez-Felipe et al.
Self-harm is an increasing public health problem with high prevalence rates in adolescents. Furthermore, it can be an indicator of different mental health disorders (e.g., depression). Recently, diverse computational methods have leveraged ...
Observe, align, and enhance: a hierarchical retrieval-augmented vision-language model for generating radiology reports [0.03%]
观察、对齐与增强：一种层次检索增强的视觉-语言模型用于生成放射学报告
Kai Chen,Xiwen Zhu,Wentai Zhang et al.
Kai Chen et al.
Radiology Report Generation (RRG) is designed to automatically generate diagnostic narratives based on radiological image interpretation, supporting clinicians in making diagnoses and relieving radiologists of reporting pressure. Previous a...
Reconstructing brain causal dynamics for subject and task fingerprints using fMRI time-series data [0.03%]
基于fMRI时间序列数据重建大脑因果动力学以获取受试者和任务特征标识符
Dachuan Song,Li Shen,Duy Duong-Tran et al.
Dachuan Song et al.
Purpose: Recently, there has been a revived interest in system neuroscience causation models, driven by their unique capability to unravel complex relationships in multi-scale brain networks. In this paper, we present a n...
GradCAM as an explicability method to evaluate the performance of deep learning models in classifying pediatric arteriovenous malformations (AVM) in arterial spin labeling sequences (ASL) [0.03%]
基于深度学习的GradCAM方法在儿科动静脉畸形分类中的可解释性研究
Júlia Romagosa,Christian Mata,Raúl Benítez et al.
Júlia Romagosa et al.
Purpose: The study investigates the usefulness of Convolutional Neural Networks (CNNs) in accurately detecting arteriovenous malformations in pediatric medical imaging, particularly using arterial spin labeling sequences....
Evaluating topological and graph-theoretical approaches to extract complex multimodal brain connectivity patterns in multiple sclerosis [0.03%]
评估拓扑和图理论方法提取多发性硬化症复杂多模态脑连接模式的效果
Toni Lozano-Bagén,Eloy Martinez-Heras,Giuseppe Pontillo et al.
Toni Lozano-Bagén et al.
Brain networks, or graphs, derived from magnetic resonance imaging (MRI) offer a powerful framework for representing the structural, morphological, and functional organization of the brain. Graph-theoretical metrics have been widely employe...
CTGFusionNet: fusion of deep learning models for predicting fetal distress-a multimodal approach [0.03%]
基于深度学习的胎儿窘迫预测模型CTGFusionNet研究
P P Aswathi Mohan,V Uma,R Sasirekha et al.
P P Aswathi Mohan et al.
Cardiotocography (CTG) is a widely used technique for fetal monitoring. This study presents CTGFusionNet, a novel multimodal adaptive framework designed for prenatal analysis. The framework integrates attention-based adaptive Bi-Directional...