Using large language models as decision support tools in emergency ophthalmology [0.03%]
在紧急眼科中将大型语言模型用作决策支持工具
Ante Kreso,Zvonimir Boban,Sime Kabic et al.
Ante Kreso et al.
Background: Large language models (LLMs) have shown promise in various medical applications, but their potential as decision support tools in emergency ophthalmology remains unevaluated using real-world cases. ...
Unified modeling language for patient-centered telerehabilitation: A comprehensive framework integrating medical and biopsychosocial pathways [0.03%]
以患者为中心的远程康复统一建模语言：整合医学和生物心理社会途径的综合框架
Thomas Roy,Aurélie Bertaux,Ouassila Labbani Narsis et al.
Thomas Roy et al.
Background: Effective telerehabilitation requires robust, standardized models to ensure comprehensive and continuous patient monitoring. However, existing rehabilitation models often lack integration, failing to cover the...
Development and validation of explainable machine learning models for female hip osteoporosis using electronic health records [0.03%]
使用电子健康记录为女性髋部骨质疏松症开发和验证可解释的机器学习模型
Wanlin Jin,Lulu Xu,Chun Yue et al.
Wanlin Jin et al.
Background: Hip fractures are associated with reduced mobility, and higher morbidity, mortality, and healthcare costs. Approximately 90% of hip fractures in the elderly are associated with osteoporosis, making it particul...
Clinical decision support systems in mental health: A scoping review of health professionals' experiences [0.03%]
精神健康领域的临床决策支持系统：针对卫生专业人员体验的范围审查
Fangziyun Tong,Reeva Lederman,Simon D&#x;Alfonso
Fangziyun Tong
Background: Clinical decision support systems (CDSSs) have the potential to assist health professionals in making informed and cost-effective clinical decisions while reducing medical errors. However, compared to physical...
Machine learning explainability for survival outcome in head and neck squamous cell carcinoma [0.03%]
头颈部鳞状细胞癌生存结果的机器学习可解释性分析
Rasheed Omobolaji Alabi,Antti A Mäkitie,Mohammed Elmusrati et al.
Rasheed Omobolaji Alabi et al.
Background: Diagnosis and treatment of head and neck squamous cell carcinoma (HNSCC) induces psychological variables and treatment-related toxicity in patients. The evaluation of outcomes is warranted for effective treatm...
LinkR: An open source, low-code and collaborative data science platform for healthcare data analysis and visualization [0.03%]
LinkR：用于医疗数据分析和可视化的开源、低代码协作数据科学平台
Boris Delange,Benjamin Popoff,Thibault Séité et al.
Boris Delange et al.
Background: The development of Clinical Data Warehouses (CDWs) has greatly increased access to big data in medical research. However, the lack of standardization among different data models hampers interoperability and, c...
Mohammadhiwa Abdekhoda,Pegah Morovati
Mohammadhiwa Abdekhoda
Introduction: In the era of electronic health records, incorporating electronic prescribing is imperative to improve healthcare quality and safeguard patient well-being. Therefore, it becomes essential to recognize the in...
Anna Winkler,Martin Pallauf,Simon Krutter et al.
Anna Winkler et al.
Purpose: Falls and pressure ulcers are serious complications impacting care quality in nursing homes. Sensor technologies can help prevent these adverse events through continuous monitoring and timely intervention. This s...
AI-based personalized real-time risk prediction for behavioral management in psychiatric wards using multimodal data [0.03%]
基于AI的个性化实时风险预测在精神科病房中使用多模态数据进行行为管理
Ri-Ra Kang,Yong-Gyom Kim,Minseok Hong et al.
Ri-Ra Kang et al.
Background: Suicide is a major global health issue, with approximately 700,000 deaths annually (WHO). In psychiatric wards, managing harmful behaviors such as suicide, self-harm, and aggression is essential to ensure pati...
Patient consent for the secondary use of health data in artificial intelligence (AI) models: A scoping review [0.03%]
人工智能(AI)模型中健康数据二次利用的患者同意：范围审查
Khadijeh Moulaei,Saeed Akhlaghpour,Farhad Fatehi
Khadijeh Moulaei
Background: The secondary use of health data for training Artificial Intelligence (AI) models holds immense potential for advancing medical research and healthcare delivery. However, ensuring patient consent for such util...