A data fusion deep learning approach for accurate organelle-based classification of cancer cells [0.03%]
一种基于细胞器的精确癌症细胞分类的数据融合深度学习方法
Harrison Yee,Megan Bouyea,Joshua Goldwag et al.
Harrison Yee et al.
Purpose: Microscopy-based cancer cell classification traditionally relies on cell-based morphological features, while subcellular organelle organization remains underutilized. Existing machine learning methods often requi...
Big data in healthcare and medicine revisited design and managerial challenges in the age of artificial intelligence [0.03%]
大数据在医疗保健和医学中的再思考人工智能时代的设计与管理挑战
Wullianallur Raghupathi,Viju Raghupathi
Wullianallur Raghupathi
A decade ago, we characterized big data in healthcare as a nascent field anchored in distributed computing paradigms. The intervening years have witnessed a transformation so profound that revisiting our original framework is essential. Thi...
Pose2met: a unified spatiotemporal framework for 3D human pose estimation and energy expenditure estimation [0.03%]
姿态估计与能量消耗估计一体化框架
Zhongteng Zhang,Liu Zhang,Qing Peng et al.
Zhongteng Zhang et al.
Purpose: This study addresses key challenges in 3D human pose estimation (HPE) and energy expenditure estimation (EEE), focusing on handling complex activities, improving generalization, and jointly enhancing both tasks w...
Exploring the potential of large language models in healthcare: a focus on cardiovascular disease analysis [0.03%]
探究大型语言模型在医疗领域的潜力：以心血管疾病分析为重点
Aihua Li,Xinran Bi,Sifan Chen et al.
Aihua Li et al.
Objective: With the rapid development of big data and artificial intelligence technologies, large language models (LLMs) are increasingly being applied across multiple fields. In the healthcare domain, efficient utilizati...
Optimizing ED patient disposition predictions through clinical narratives with advanced pre-trained language models [0.03%]
通过临床叙述和高级预训练语言模型优化急诊科患者的处置预测
Mei-Hui Lee,Ting-Yun Huang,Pei-Ying Yang et al.
Mei-Hui Lee et al.
Timely identification of febrile patients requiring hospitalization remains a significant challenge in Emergency Departments (EDs), with delayed intervention potentially increasing mortality. This retrospective study presents a novel approa...
Machine learning models for volume and weight estimation in breast reconstruction planning [0.03%]
乳腺重建规划中的体积和重量估算的机器学习模型
Sheng-Pu Teo,Mee-Hoong See,Lee-Lee Lai et al.
Sheng-Pu Teo et al.
Background: Accurate estimation of breast volume and weight is critical for post-mastectomy reconstruction. Existing methods are frequently costly or complex. We developed a machine learning framework that leverages demog...
Large language models and conditional rules in clinical decision support systems [0.03%]
大型语言模型与临床决策支持系统的条件规则
Shangeetha Sivasothy,Adrian Bingham,Irini Logothetis et al.
Shangeetha Sivasothy et al.
Background: Clinical Decision Support Systems (CDSS) improve patient outcomes and support sustainable health services by enhancing medical decisions. Developing rules for a CDSS is expensive due to delays in capturing and...
Caner Ozer,Arda Guler,Aysel Turkvatan Cansever et al.
Caner Ozer et al.
Purpose: Medical image quality assessment is crucial, as poor-quality images can lead to misdiagnosis. Manual quality labeling is tedious for large studies and may produce misleading results. While automated analysis of i...
HeteroMed: a heterogeneous graph knowledge-enhanced model for medication recommendation [0.03%]
异构图知识增强的药物推荐模型HeteroMed
Xuelei Yin,Mengzhu Liu,Zaiquan Dong et al.
Xuelei Yin et al.
Medication recommendation aims to generate treatment regimens that balance efficacy and safety based on patients' historical medical records. Recent studies leveraging longitudinal Electronic Health Records (EHR) sequence modeling have sign...
Healthcare utilization and chronic condition clusters in multimorbidity patients using weighted k-means: a register-based study in Denmark [0.03%]
基于丹麦注册资料的多发病患者的医疗利用与慢性病聚类特征研究：加权K均值法的应用
Danny J Anthonimuthu,Nikolaj N Holm,Anders Stockmarr et al.
Danny J Anthonimuthu et al.
Background: The growing burden of multimorbidity challenges the healthcare system due to increased healthcare utilization and uncoordinated care. Identifying patients with multimorbidity who have high healthcare utilizati...