Voice Analysis and Neural Networks as a Clinical Decision Support System for Patients With Lung Diseases [0.03%]
基于语音分析和神经网络的临床决策支持系统在肺疾病患者中的应用
Kamilla A Bringel,Davi C M G Leone,João Vitor L de C Firmino et al.
Kamilla A Bringel et al.
Objective: To analyze the voice of patients with lung diseases, compared with healthy individuals, to detect patterns capable of assessing dyspnea using artificial neural networks (ANNs). ...
Judd E Hollander,Kristin L Rising,Brian M Dougan
Judd E Hollander
Information and Communication Technology to Enhance the Implementation of the Integrated Management of Childhood Illness: A Systematic Review and Meta-Analysis [0.03%]
一项系统评价和网络 meta 分析：利用信息和通讯技术加强对儿童疾病综合管理实施的影响
Andrea Bernasconi,Marco Landi,Clarence S Yah et al.
Andrea Bernasconi et al.
Objective: To evaluate the impact of Information and Communication Technology (ICT) on the implementation of Integrated Management of Childhood Illness (IMCI) and integrated Community Case Management (iCCM) through a syst...
Staff Experiences Transitioning to Digital Dermatopathology in a Tertiary Academic Medical Center: Lessons Learned From Implementation Science [0.03%]
美国三级学术医学中心皮肤病理学数字化转型中员工的体验及实施科学中的经验教训
Celia C Kamath,Erin O Wissler Gerdes,Barbara A Barry et al.
Celia C Kamath et al.
Digital pathology (DP) transforms practice by replacing traditional glass slide review with digital whole slide images and workflows. Although digitization may improve accuracy and efficiency, transitioning to digital practice requires staf...
[This corrects the article DOI: 10.1016/j.mcpdig.2023.07.003.]. © 2024 The Authors.
How are Machine Learning and Artificial Intelligence Used in Digital Behavior Change Interventions? A Scoping Review [0.03%]
机器学习和人工智能在数字行为干预中的应用：综述研究
Amy Bucher,E Susanne Blazek,Christopher T Symons
Amy Bucher
To assess the current real-world applications of machine learning (ML) and artificial intelligence (AI) as functionality of digital behavior change interventions (DBCIs) that influence patient or consumer health behaviors. A scoping review ...
[This corrects the article DOI: 10.1016/j.mcpdig.2023.06.009.]. © 2024 The Authors.
Performance of 5 Prominent Large Language Models in Surgical Knowledge Evaluation: A Comparative Analysis [0.03%]
五种主流语言模型在外科知识评估中的表现：比较分析
Adam M Ostrovsky,Joshua R Chen,Vishal N Shah et al.
Adam M Ostrovsky et al.
Deep Learning-Based Prediction of Hepatic Decompensation in Patients With Primary Sclerosing Cholangitis With Computed Tomography [0.03%]
基于深度学习和CT图像预测原发性硬化性胆管炎患者肝衰竭风险
Yashbir Singh,Shahriar Faghani,John E Eaton et al.
Yashbir Singh et al.
Objective: To investigate a deep learning model for predicting hepatic decompensation using computed tomography (CT) imaging in patients with primary sclerosing cholangitis (PSC). ...
Electrocardiogram Signal Analysis With a Machine Learning Model Predicts the Presence of Pulmonary Embolism With Accuracy Dependent on Embolism Burden [0.03%]
一种机器学习模型通过分析心电图信号预测肺栓塞的准确度依赖于栓塞负荷大小
Waldemar E Wysokinski,Ryan A Meverden,Francisco Lopez-Jimenez et al.
Waldemar E Wysokinski et al.
Objective: To develop an artificial intelligence deep neural network (AI-DNN) algorithm to analyze 12-lead electrocardiogram (ECG) for detection of acute pulmonary embolism (PE) and PE categories. ...