Automated Bone Age Assessment and Adult Height Prediction from Pediatric Hand Radiographs via a Cascaded Deep Learning Framework [0.03%]
基于串联深度学习框架的儿童骨龄自动评估及成人期身高预测方法
Nihui Pei,Yijiang Zhuang,Zhe Su et al.
Nihui Pei et al.
Bone age assessment and adult height prediction are essential for evaluating pediatric growth. Traditional methods rely on manual radiographic interpretation, which is subjective, time-consuming, and prone to inter-observer variability. Thi...
Computational Framework for Structuring and Analyzing Clinical Trial Criteria for AI-Guided Fine-grained Matching [0.03%]
用于AI引导的细粒度匹配的临床试验标准结构和分析的计算框架
Daniel R S Habib,Ishan Mahajan,Betina Evancha et al.
Daniel R S Habib et al.
While artificial intelligence (AI) has demonstrated potential in automating clinical trial matching, most existing solutions rely on high-level structured data or oversimplified criteria. This study introduces a framework to structure and a...
Infectious, Allergic, and Immune-Mediated Disease Data Resources: a Landscape Overview and Subset Assessment [0.03%]
传染病、过敏和免疫介导疾病的数据资源：概览与子集评估
Darya Pokutnaya,Lisa M Mayer,Sydney Foote et al.
Darya Pokutnaya et al.
The Data Management and Sharing (DMS) Policy issued by the National Institutes of Health (NIH) requires most grant applications to include a DMS Plan, detailing data type(s), resources (e.g., data repositories, knowledgebases, portals) for ...
Logic-based Approach and Visualization for the Nuclear Medicine Rescheduling Problem [0.03%]
基于逻辑的核医学重新调度问题的方法及可视化技术
Cinzia Marte,Marco Mochi,Carmine Dodaro et al.
Cinzia Marte et al.
The Nuclear Medicine Scheduling problem consists of assigning patients to a day, on which the patient will undergo the medical check, the preparation, and the actual image detection process. The schedule of the patients should consider thei...
Predictive Performance of Raman Spectroscopy in Osteoarthritis: A Systematic Review [0.03%]
拉曼光谱预测骨关节炎疗效的系统评价研究进展
Monira Yesmean,Bijay Ratna Shakya,Minna Mannerkorpi et al.
Monira Yesmean et al.
Early diagnosis of osteoarthritis (OA) remains a critical unmet need due to the lack of reliable detection methods. Detecting OA at an early stage provides a valuable clinical window for implementing effective intervention strategies. Raman...
Eunmi Bae,Arum Moon,Seungju Baek et al.
Eunmi Bae et al.
In South Korea, over half the adults are insufficiently active. Mobile health (mHealth) interventions can increase physical activity. This study evaluated the cost-effectiveness of a smartwatch and smartphone application to promote moderate...
Requirements for Manual Knowledge Acquisition Tools: Systematic Literature Review and Expert Panel Consensus [0.03%]
关于手动知识获取工具需求的系统性文献回顾及专家共识
N van Brummelen,J H Leopold,S Medlock
N van Brummelen
Knowledge acquisition tools facilitate the creation and maintenance of decision support content, but thus far there is little formal investigation of the requirements and desiderata for such tools. This leads to researchers re-inventing the...
A Dual-stage Deep Learning Framework for Breast Ultrasound Image Segmentation and Classification [0.03%]
一种用于乳腺超声图像分割和分类的双阶段深度学习框架
Pierangela Bruno,Megan Macrì,Carmine Dodaro
Pierangela Bruno
Deep Learning methods have become a powerful tool in medical imaging, with great potential to improve diagnostic accuracy and support early disease detection. This is especially critical for breast cancer, one of the most common cancers amo...
Diffusion Models for Neuroimaging Data Augmentation: Assessing Realism and Clinical Relevance [0.03%]
用于神经影像数据增强的扩散模型：评估逼真度和临床相关性
Giulio Mallardi,Fabio Calefato,Filippo Lanubile et al.
Giulio Mallardi et al.
Data scarcity remains a major obstacle to the application of deep learning techniques in medical imaging, particularly for rare neurodegenerative diseases. This study investigates the use of denoising diffusion probabilistic models (DDPMs) ...