Artificial intelligence guided dosing decisions: a qualitative study on health care provider perspectives [0.03%]
基于人工智慧的给药决策：医疗卫生人员视角的定性研究
Jennifer Sumner,Jaminah Mohamed Ali,Mehul Motani et al.
Jennifer Sumner et al.
Objectives: Tailoring medication dosing to an individual's traits is complex, but artificial intelligence (AI) advancements enable greater precision. Our study objectives were to gauge healthcare providers' perspectives o...
Enhancing medication safety with System Approach to Verifying Electronic Prescriptions (SAV E-Rx): pharmacists' review of product selection outcomes between prescribed and dispensed medications [0.03%]
用药系统核验电子处方方法改善药物安全性：药房药师审查开具药品与发出药品之间的选择结果差异性分析
Jun Gong,Vincent D Marshall,Megan Whitaker et al.
Jun Gong et al.
Objectives: Electronic prescriptions (e-prescriptions) introduce drug product selection mismatches during pharmacy data entry. System Approach to Verifying Electronic Prescriptions (SAV E-Rx) detects and alerts pharmacy s...
Supporting cancer research on real-world data: extracting colorectal cancer status and explicitly written TNM stages from free-text imaging and histopathology reports [0.03%]
基于真实世界数据支持癌症研究：从影像和病理报告的自由文本中提取结直肠癌状态及明确书写的TNM分期
Andres Tamm,Helen J S Jones,Neel Doshi et al.
Andres Tamm et al.
Objectives: The 'tumour, node, metastasis' (TNM) classification of colorectal cancer (CRC) predicts prognosis and so is vital to consider in analyses of patterns and outcomes of care when using electronic health records. ...
Use, knowledge and perception of large language models in clinical practice: a cross-sectional mixed-methods survey among clinicians in Switzerland [0.03%]
瑞士临床医生在临床实践中使用、知识和感知大型语言模型的横断面混合方法调查
Simon Bruno Egli,Armon Arpagaus,Simon Adrian Amacher et al.
Simon Bruno Egli et al.
Objectives: Large language model (LLM)-based tools offer potential for clinical practice but raise concerns regarding output accuracy, patient safety and data security. We aimed to assess Swiss clinicians' use, knowledge ...
Comparative performance of logistic regression, multilayer perceptron and decision tree models for predicting surgical pressure injuries: a retrospective cohort study [0.03%]
逻辑回归、多层感知器和决策树模型预测手术压力性损伤的比较分析：回顾性队列研究
Chia-Yen Li,Chi-Ming Chu,Chao-Wen Chen et al.
Chia-Yen Li et al.
Objectives: Surgical pressure injuries (SPIs) are a significant patient safety risk due to prolonged immobility and tissue hypoperfusion under general anaesthesia. Existing risk assessment tools lack real-time predictive ...
Comparative Study
BMJ health & care informatics. 2025 Sep 17;32(1):e101532. DOI:10.1136/bmjhci-2025-101532 2025
Real-time activity and fall detection using transformer-based deep learning models for elderly care applications [0.03%]
基于变压器的深度学习模型在老年人护理应用中的实时活动和跌倒检测
Raja Omman Zafar,Farhan Zafar
Raja Omman Zafar
Objective: This study aims to develop a transformer-based deep learning model for real-time activity recognition and fall detection, addressing the limitations of existing methods in terms of accuracy and real-time applic...
Feasibility of semiautomated surveillance of healthcare-associated Staphylococcus aureus bloodstream infections using hospital electronic health records in Victoria, Australia [0.03%]
基于澳大利亚维多利亚州医院电子健康记录的医疗相关金黄色葡萄球菌血流感染半自动化监测可行性研究
Lyn-Li Lim,Stephanie K Tanamas,Ann Bull et al.
Lyn-Li Lim et al.
Objective: Many hospitals struggle to transform electronic health record (EHR) data to support performance, continuous improvement and patient safety. Our study aimed to explore the feasibility of semiautomated surveillan...
Implementation of patient safety monitoring systems in hospitals: a systematic review [0.03%]
医院患者安全监控系统的实施:系统综述研究
Ghasem Alizadeh-Dizaj,Shahla Damanabi,Mohammad Esmaeil Hejazi et al.
Ghasem Alizadeh-Dizaj et al.
Background: The significance of patient safety has been acknowledged in healthcare systems, prompting the need for effective patient safety monitoring systems (PSMSs). These systems' endeavour is to manage patient safety ...
Automated sepsis prediction from unstructured electronic health records using natural language processing: a retrospective cohort study [0.03%]
基于自然语言处理的电子健康记录中未结构化数据的自动化序贯器官衰竭评估预测：回顾性队列研究
Lipi Mishra,Sowmya Muchukunte Ramaswamy,Broderick Ivan McCallum-Hee et al.
Lipi Mishra et al.
Objective: Artificial intelligence (AI) holds promise for predicting sepsis. However, challenges remain in integrating AI, natural language processing (NLP) and free text data to enhance sepsis diagnosis at emergency depa...
Data as medicine's backbone: redefining its value to foster innovation in the data economy [0.03%]
数据铸就医药业的脊梁：重新定义其价值以促进数据经济创新
Michael Byczkowski
Michael Byczkowski
Data are the engine of modern medicine, yet its economic trade-off remains unequally distributed: hospitals and research institutions shoulder the effort of collection, while life science companies reap the financial rewards. This imbalance...