Accuracy, Efficiency, and usability of a Semi-Automated SMART on FHIR venous thromboembolism risk assessment App: A randomised crossover simulation study [0.03%]
一种半自动的基于SMART on FHIR的静脉血栓栓塞症风险评估程序的准确性、效率和适用性：随机交叉模拟试验
Marie Cahill,Fergal O&#x;Shaughnessy,Fiona Boland et al.
Marie Cahill et al.
Background: Venous thromboembolism (VTE) is the leading cause of maternal death. Current VTE risk assessment (VTERA) tools often require manual data entry, which can reduce accuracy and affect thromboprophylaxis decisions...
From algorithmic innovation to clinical deployment: A systematic review of methodological gaps limiting federated learning in healthcare [0.03%]
从算法创新到临床应用：系统性回顾联邦学习在医疗健康领域的理论与实践差距
Sandhya Vijayasarathy
Sandhya Vijayasarathy
Objective: Federated learning (FL) is a distributed machine learning paradigm designed to enable model training across decentralized data sources without requiring data centralization. This review critically examines FL a...
Accuracy and completeness of large language models in Epidemic keratoconjunctivitis Queries: A Comparative study [0.03%]
大规模语言模型在流行性角结膜炎查询中的准确性和完整性比较研究
Acieh Es&#x;haghi,Mohsen Aliyariparand,Kaveh Jamalipour Soufi et al.
Acieh Es&#x;haghi et al.
Background: Large language models (LLMs) are increasingly applied in clinical contexts, yet their reliability in disease-specific ophthalmic domains remains insufficiently characterized. Epidemic keratoconjunctivitis (EKC...
Machine learning for site risk prediction in clinical trials: development, external validation, and operational application in site qualification [0.03%]
临床试验中的研究者风险预测的机器学习方法：开发，外部验证及在研究机构资质评估中的应用
Zhiwen Yang
Zhiwen Yang
Background: Site selection and qualification represent critical operational challenges in clinical trials, particularly in rare diseases like transthyretin amyloid cardiomyopathy (ATTR-CM)-a progressive cardiac disease ca...
Human in the loop artificial intelligence in healthcare: applications, outcomes, and implementation challenges [0.03%]
医疗保健中的人工智能：应用、结果与实施挑战
David B Olawade,Shamiul Bashir Plabon,Adeyinka Ojo et al.
David B Olawade et al.
Background: The integration of artificial intelligence in healthcare has transformed clinical practice and research methodologies. However, concerns regarding algorithmic accountability, interpretability, and safety have ...
Enhancing fairness and standardization in AI-versus-physician diagnostic comparisons: A scoping review [0.03%]
提升人工智能与医师诊断比较的公平性和标准化：综述研究
Xun Chen,Hewen Xu,Ying Huang et al.
Xun Chen et al.
Objective: The growing number of studies directly comparing artificial intelligence (AI) to physicians in diagnostic tasks often focuses on performance outcomes, overlooking fundamental methodological rigor. This scoping ...
Transforming nursing documentation data into the Observational Medical Outcomes Partners common data model [0.03%]
护理文件数据转换为观察医疗结果合作组织通用数据模型
Hyesil Jung,Sooyoung Yoo,Seok Kim et al.
Hyesil Jung et al.
Background: Electronic health records (EHRs) provide clinical evidence for observational studies. Of these, nursing documentation data reflect patients' problems or situations and nursing services that are not available f...
Comparison of model Predictive control (MPC) algorithms to optimise blood glucose in fully closed loop (FCL) systems [0.03%]
模型预测控制(MPC)算法在全闭环(FCL)系统中优化血糖的比较研究
Neil Vaughan,Aaisha Rashid
Neil Vaughan
Background and aims: Model Predictive Control (MPC) is emerging within fully closed loop (FCL) systems to offer a promising advancement, by automating glucose regulation for people with Type 1 Diabetes. This article asses...
Healthcare practitioner involvement in data-driven clinical decision support development and evaluation: Critical narrative review of recommendations [0.03%]
基于数据的临床决策支持工具的开发与评估中医疗从业者参与度的重要叙述性回顾及建议
Ruth P Evans,Louise D Bryant,Gregor Russell et al.
Ruth P Evans et al.
Objective: While healthcare practitioner (HCP) involvement is widely acknowledged as essential for the development and evaluation of trustworthy data-driven clinical decision support systems (CDSS), practical guidance rem...
Validity of a novel web application for measuring active range of motion and its reliability as a self-measurement method in telerehabilitation [0.03%]
一种新型web应用程序有效性的验证及其作为远程康复自我测量方法的可靠性研究
Jesús Aguiló-Furió,Borja Tronchoni-Crespo,Noemí Moreno-Segura et al.
Jesús Aguiló-Furió et al.
Purpose: As a result of the emergence of Artificial Intelligence (AI), new applications for measuring active range of motion (AROM) in telerehabilitation (TR) are being developed. The main objectives of the present study ...