Kenneth Lau,Jana Tumova,David Broman et al.
Kenneth Lau et al.
State-of-the-art radiotherapy machines with integrated magnetic resonance (MR) imaging, known as MR-Linacs, provide the capability to track tumors in real time. This capability aids delivery of precise irradiation in the presence of patient...
Multimodal biomarker AI techniques for early neurocognitive disorder diagnosis: A systematic review [0.03%]
多模态生物标志物AI技术在神经认知障碍早期诊断中的应用：系统性综述
Feliciana Catino,Fabio Castellana,Roberta Zupo et al.
Feliciana Catino et al.
Background: Early diagnosis of Alzheimer's disease (AD) and related dementias remains challenging because no single biomarker sufficiently captures the complex and multifactorial nature of the underlying pathology. In rec...
Identifying and timing patient outcomes in clinician notes using large language models [0.03%]
使用大型语言模型在临床医师记录中识别和确定患者结果的时间
Tassallah Abdullahi,Ali Hamzeh,Isaac Sears et al.
Tassallah Abdullahi et al.
Background: Key challenges in leveraging unstructured clinician notes for predictive models include identifying and timing patient outcomes. To address these challenges we applied large language models (LLMs) to identify ...
Machine learning-based methods for predicting postpartum depression: A review [0.03%]
基于机器学习的预测产后抑郁方法综述
Xiaobo Zhang,Jinyu Bao,Jianzhong Ye et al.
Xiaobo Zhang et al.
Postpartum depression (PPD) is a widespread mental illness after delivery, which has a substantial impact on the health of both mothers and infants. Machine learning (ML) has developed rapidly and plays a vital function in disease predictio...
Comment on: "Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces" [0.03%]
关于“腹部主动脉瘤表面局部增长的几何深度学习预测”的评论
Antonio Bozzani,Pietro Cerveri,Vittorio Arici et al.
Antonio Bozzani et al.
An artificial intelligence approach to support adolescent suicide prevention initiatives in the United States [0.03%]
美国青少年自杀预防的人工智能方法研究
Luke Liang,Ryan Schuerkamp,Ketra L Rice et al.
Luke Liang et al.
Adolescent suicide remains a critical public health issue in the United States, with complex, interrelated risk and protective factors operating across multiple levels of the social ecology. This study presents the design of a novel agent-b...
PDAFormer 3+: A full-scale connected modified transformer with parallel dual attention for 3D medical image segmentation [0.03%]
PDAFormer 3+: 带有并行双注意的全连接修改变压器，用于3D医学图像分割
Jinhui Zhang,Yueyang Gao,Jian Liu et al.
Jinhui Zhang et al.
Medical image segmentation is essential for enhancing diagnostic and therapeutic accuracy, improving healthcare efficiency, and advancing medical research. In recent years, transformers have gained increasing attention in medical image segm...
Systematic review of Artificial Intelligence-based methods for glycemic control and risk prediction in intensive care units [0.03%]
基于人工智能的危重病患者血糖控制和风险预测的方法综述
Muhammad Abdullah Sarwar,Robertas Damaševičius,Eglė Belousovienė et al.
Muhammad Abdullah Sarwar et al.
Background: Achieving safe glycemic targets in intensive care remains difficult due to rapidly changing physiology, treatment effects, and measurement noise. ...
PatientFlow: Learning to generate mixed-type longitudinal clinical data with flow matching [0.03%]
PatientFlow：利用流匹配生成混合类型的纵向临床数据
Ruben Branco,Marta Gromicho,Mamede de Carvalho et al.
Ruben Branco et al.
Synthetic longitudinal clinical data, with static and temporal mixed-type components, can help unlock large-scale deep learning models to tackle complex diseases. However, learning to generate realistic patients faces dual challenges: model...
TabulaTime: Novel multimodal deep learning for Acute Coronary Syndrome prediction through environmental and clinical data integration [0.03%]
基于环境和临床数据融合的急性冠状动脉综合征预测的新型多模态深度学习方法
Xin Zhang,Liangxiu Han,Saad Hassan et al.
Xin Zhang et al.
Acute Coronary Syndromes (ACS), including ST- and non-ST-segment elevation myocardial infarction (STEMI, NSTEMI), remain a leading cause of global mortality. Traditional Cardiovascular Risk Scores (CVRS) provide important insights but mainl...