Preoperative Prediction of Perineural Invasion in Pancreatic Ductal Adenocarcinoma Using Machine Learning Radiomics Based on Contrast-Enhanced CT Imaging [0.03%]
基于增强CT影像的机器学习影像组学预测胰腺导管腺癌术前肿瘤神经侵犯
Wenzheng Lu,Yanqi Zhong,Xifeng Yang et al.
Wenzheng Lu et al.
The objective of the study is to assess the clinical value of machine learning radiomics based on contrast-enhanced computed tomography (CECT) images in preoperative prediction of perineural invasion (PNI) status in pancreatic ductal adenoc...
The Impact of Artificial Intelligence on Radiologists' Reading Time in Bone Age Radiograph Assessment: A Preliminary Retrospective Observational Study [0.03%]
人工智能在骨龄X线评估中对放射科医生阅片时间影响的初步回顾性研究
Sejin Jeong,Kyunghwa Han,Yaeseul Kang et al.
Sejin Jeong et al.
To evaluate the real-world impact of artificial intelligence (AI) on radiologists' reading time during bone age (BA) radiograph assessments. Patients (
Cone-Beam CT to CT Image Translation Using a Transformer-Based Deep Learning Model for Prostate Cancer Adaptive Radiotherapy [0.03%]
基于变压器的深度学习模型用于前列腺癌适应性放射治疗的锥束CT到CT图像转换
Yuhei Koike,Hideki Takegawa,Yusuke Anetai et al.
Yuhei Koike et al.
Cone-beam computed tomography (CBCT) is widely utilized in image-guided radiation therapy; however, its image quality is poor compared to planning CT (pCT), thus restricting its utility for adaptive radiotherapy (ART). Our objective was to ...
A Comparative Evaluation of Large Language Model Utility in Neuroimaging Clinical Decision Support [0.03%]
大型语言模型在神经影像临床决策支持中的效用比较评估
Luke Miller,Peter Kamel,Jigar Patel et al.
Luke Miller et al.
Imaging utilization has increased dramatically in recent years, and at least some of these studies are not appropriate for the clinical scenario. The development of large language models (LLMs) may address this issue by providing a more acc...
Volumetric Integrated Classification Index: An Integrated Voxel-Based Morphometry and Machine Learning Interpretable Biomarker for Post-Traumatic Stress Disorder [0.03%]
基于体积的综合分类指数：一种用于创伤后应激障碍的可解释成像生物标志物
Yulong Jia,Beining Yang,Haotian Xin et al.
Yulong Jia et al.
PTSD is a complex mental health condition triggered by individuals' traumatic experiences, with long-term and broad impacts on sufferers' psychological health and quality of life. Despite decades of research providing partial understanding ...
Learnable Context in Multiple Instance Learning for Whole Slide Image Classification and Segmentation [0.03%]
用于整张幻灯片图像分类和分割的多示例学习中的上下文可学习性
Yu-Yuan Huang,Wei-Ta Chu
Yu-Yuan Huang
Multiple instance learning (MIL) has become a cornerstone in whole slide image (WSI) analysis. In this paradigm, a WSI is conceptualized as a bag of instances. Instance features are extracted by a feature extractor, and then a feature aggre...
Diagnostic Performance of a Next-Generation Virtual/Augmented Reality Headset: A Pilot Study of Diverticulitis on CT [0.03%]
下一代虚拟/增强现实头戴式显示设备的诊断性能：一项关于CT结肠憩室炎的试点研究
Paul M Murphy,Julie Y An,Luke M Wojdyla et al.
Paul M Murphy et al.
Next-generation virtual/augmented reality (VR/AR) headsets may rival the desktop computer systems that are approved for clinical interpretation of radiologic images, but require validation for high-resolution low-luminance diagnoses like di...
A Multi-model Deep Learning Architecture for Diagnosing Multi-class Skin Diseases [0.03%]
一种用于诊断多类皮肤病的多模型深度学习架构
Mohamed Badr,Abdullah Elkasaby,Mohammed Alrahmawy et al.
Mohamed Badr et al.
Skin diseases are a significant global public health concern, affecting 21-85% of the world's population, particularly those in low- and middle-income countries. Accurate and timely diagnosis is crucial for effective treatment and improved ...
Applying Deep-Learning Algorithm Interpreting Kidney, Ureter, and Bladder (KUB) X-Rays to Detect Colon Cancer [0.03%]
应用深度学习算法解读肾、输尿管和膀胱X射线以检测结肠癌
Ling Lee,Chin Lin,Chia-Jung Hsu et al.
Ling Lee et al.
Early screening is crucial in reducing the mortality of colorectal cancer (CRC). Current screening methods, including fecal occult blood tests (FOBT) and colonoscopy, are primarily limited by low patient compliance and the invasive nature o...
SDS-Net: A Synchronized Dual-Stage Network for Predicting Patients Within 4.5-h Thrombolytic Treatment Window Using MRI [0.03%]
一种用于预测符合条件的卒中溶栓患者的同步双阶段网络
Xiaoyu Zhang,Ying Luan,Ying Cui et al.
Xiaoyu Zhang et al.
Timely and precise identification of acute ischemic stroke (AIS) within 4.5 h is imperative for effective treatment decision-making. This study aims to construct a novel network that utilizes limited datasets to recognize AIS patients withi...