Continuous and componentized facial palsy measurement alignment and clinical interpretable model [0.03%]
连续且模块化的面部瘫痪测量对齐和临床可解释模型
Xiudong Guan,Haixin Wang,Dainan Zhang et al.
Xiudong Guan et al.
Facial palsy, affecting 1 in 60 individuals, requires precise assessment for effective treatment and follow-up. Current grading systems are inconsistent due to redundant subjective factors. Discrete assessment of the whole face fails to add...
Interpretable Multiomics Models for Predicting Surgical Interventions and Blood Transfusion Requirements in Traumatic Brain Injury [0.03%]
可解释的多组学模型在预测创伤性脑损伤手术干预和输血需求中的应用
Jiang Deng,Tao Deng,Yan-Chun Zhang et al.
Jiang Deng et al.
Accurately predicting surgical and transfusion needs in traumatic brain injury (TBI) patients remains challenging in emergency settings. We developed multiomics data fusion (MDF) models integrating clinical biomarkers, neural radiological i...
Artificial intelligence prediction of age from echocardiography as a marker for cardiovascular disease [0.03%]
基于超声心动图的年龄人工智能预测作为心血管疾病的标志物
Meenal Rawlani,Hirotaka Ieki,Christina Binder et al.
Meenal Rawlani et al.
While chronological age is a universal risk predictor across most populations and diseases, distinguishing between biologically older from younger individuals may identify individuals with accelerated or delayed cardiovascular aging. This s...
Virtual nature, real relief: how exposure to virtual natural environments reduces anxiety, stress, and depression in healthy adults [0.03%]
虚拟自然，真实缓解：虚拟自然环境如何减少健康成年人的焦虑、压力和抑郁症状
Lunxin Chen,Ruixiang Yan,Jialiang Yu
Lunxin Chen
Stress, anxiety, and depression represent significant challenges to global public health. Exposure to virtual natural environments, as a convenient and scalable intervention, has shown uncertain effects on healthy adults. This systematic re...
CartiSurface: implicit surface reconstruction for anatomically-aware cartilage thickness mapping in knee MRI [0.03%]
基于膝关节MRI的软骨厚度绘制的隐式表面重建方法 CARTISURFACE
Pengyun Wang,Wenpeng Zhang,Liang Li et al.
Pengyun Wang et al.
Quantitative analysis of cartilage thickness plays a pivotal role in the early diagnosis and monitoring of knee osteoarthritis (OA). However, conventional segmentation-based approaches often produce noisy and anatomically inconsistent thick...
Aarav Badani,Fabio Ynoe de Moraes,Philipp Vollmuth et al.
Aarav Badani et al.
Clinical trials face persistent challenges in cost, enrollment, and generalizability. This perspective examines how artificial intelligence (AI), large language models (LLMs), adaptive trial designs, and digital twins (DTs) can modernize tr...
Integration of artificial intelligence and wearable technology in the management of diabetes and prediabetes [0.03%]
人工智能和可穿戴技术在糖尿病和前期糖尿病管理中的整合
Raphael A Fraser,Rebekah J Walker,Jennifer A Campbell et al.
Raphael A Fraser et al.
Artificial intelligence and wearable technology are increasingly used in healthcare and hold significant potential for improving the management of diabetes. Wearable devices enable continuous monitoring and real-time data collection, suppor...
Large language models driven neural architecture search for universal and lightweight disease diagnosis on histopathology slide images [0.03%]
基于大语言模型的神经架构搜索在组织病理切片图像上的通用和轻量级疾病诊断方法
Xiu Su,Qinghua Mao,Zhongze Wu et al.
Xiu Su et al.
Artificial Intelligence has revolutionized healthcare by offering smart services and reducing diagnostic burden, particularly facilitating the identification and segmentation of malignant tissues. However, current task-specific approaches r...
Uncertainty-aware large language models for explainable disease diagnosis [0.03%]
具有不确定性意识的大规模语言模型在可解释疾病诊断中的应用
Shuang Zhou,Jiashuo Wang,Zidu Xu et al.
Shuang Zhou et al.
Explainable disease diagnosis, which leverages patient information (e.g., symptoms) and computational models to generate probable diagnoses and reasoning, holds strong clinical promise. Yet, when clinical notes lack sufficient evidence for ...
Matters arising: Utilizing foundation models for developing clinical tools [0.03%]
源于基础模型的临床工具开发中的问题探讨
Hin Yin Chan,Chak Fung Ng,Oscar Yui Ming Choi et al.
Hin Yin Chan et al.
Zhang et al. developed a RETFound-enhanced deep learning model to detect multiple eye diseases and tested it in a community-based screening setting. Nevertheless, we believe that more information could be provided to support the claim that ...