Predicting Alzheimer's disease from cognitive footprints in mid and late life: How much can register data and machine learning help? [0.03%]
利用登记数据和机器学习预测中年和老年期的认知特征以诊断阿尔茨海默病？有多大的帮助？
Hao Luo,Sirpa Hartikainen,Julian Lin et al.
Hao Luo et al.
Background: Real-world data with decades-long medical records are increasingly available alongside the growing adoption of machine learning in healthcare research. We evaluated the performance of machine learning models i...
Prediction of diabetic retinopathy among type 2 diabetic patients in University of Gondar Comprehensive Specialized Hospital, 2006-2021: A prognostic model [0.03%]
2006-2021年贡达尔大学综合医院2型糖尿病患者糖尿病视网膜病变的预测：预后模型
Tsion Mulat Tebeje,Melaku Kindie Yenit,Solomon Gedlu Nigatu et al.
Tsion Mulat Tebeje et al.
Background: There has been a paucity of evidence for the development of a prediction model for diabetic retinopathy (DR) in Ethiopia. Predicting the risk of developing DR based on the patient's demographic, clinical, and ...
Personalized prediction of intradialytic hypotension in clinical practice: Development and evaluation of a novel AI dashboard incorporating risk factors from previous and current dialysis sessions [0.03%]
基于人工智能的个性化预测透析低血压的临床实践：整合之前和当前透析会话风险因素的新型AI监测仪的研发与评估
I-Ning Yang,Chung-Feng Liu,Chih-Chiang Chien et al.
I-Ning Yang et al.
Background: Intradialytic hypotension (IDH) is one of the most common and critical complications of hemodialysis. Despite many proven factors associated with IDH, accurately predicting it before it occurs for individual p...
Self-help groups and opioid use disorder treatment: An investigation using a machine learning-assisted robust causal inference framework [0.03%]
自助团体与阿片类药物使用障碍治疗：利用机器学习辅助的稳健因果推断框架进行调查
Sahil Shikalgar,Scott G Weiner,Gary J Young et al.
Sahil Shikalgar et al.
Objectives: This study investigates the impact of participation in self-help groups on treatment completion among individuals undergoing medication for opioid use disorder (MOUD) treatment. Given the suboptimal adherence ...
Implementation and evaluation of an additional GPT-4-based reviewer in PRISMA-based medical systematic literature reviews [0.03%]
基于PRISMA的医学系统文献回顾中增加GPT-4 reviewers的实现与评估
Assaf Landschaft,Dario Antweiler,Sina Mackay et al.
Assaf Landschaft et al.
Background: PRISMA-based literature reviews require meticulous scrutiny of extensive textual data by multiple reviewers, which is associated with considerable human effort. ...
Impact of digital health on the quadruple aims of healthcare: A correlational and longitudinal study (Digimat Study) [0.03%]
数字化健康对医疗保健的四个目标的影响：相关性和纵向研究（Digimat研究）
Leanna Woods,Rebekah Eden,Damian Green et al.
Leanna Woods et al.
Background: Digital healthcare aims to deliver on the quadruple aim: enhance patient experiences, improve population health, reduce costs and improve provider experiences. Despite large investments, it is unclear how adva...
Sreejita Ghosh,Pia Burger,Mladena Simeunovic-Ostojic et al.
Sreejita Ghosh et al.
Background: Eating Disorders (EDs) are one of the most complex psychiatric disorders, with significant impairment of psychological and physical health, and psychosocial functioning, and are associated with low rates of ea...
"An excellent servant but a terrible master": Understanding the value of wearables for self-management in people with cystic fibrosis and their healthcare providers - A qualitative study [0.03%]
“优良的工具，可怕的主宰”—了解穿戴设备在囊性纤维化患者及其医疗保健提供者进行自我管理中的价值——一项定性研究
Graeme Mattison,Oliver J Canfell,Daniel Smith et al.
Graeme Mattison et al.
Background: Wearables hold potential to improve chronic disease self-management in conditions like cystic fibrosis (CF) through remote monitoring, early detection of illness and motivation. Little is known about the accep...
Predictive analysis on the factors associated with birth Outcomes: A machine learning perspective [0.03%]
基于机器学习的妊娠结局影响因素预测分析研究
Atinuke Olusola Adebanji,Clement Asare,Samuel Asante Gyamerah
Atinuke Olusola Adebanji
Background: Recent studies reveal that around 1.9 million stillbirths occur annually worldwide, with Sub-Saharan Africa having among the highest cases. Some Sub-Saharan African countries, including Ghana, failed to meet M...
Diagnostic test accuracy of externally validated convolutional neural network (CNN) artificial intelligence (AI) models for emergency head CT scans - A systematic review [0.03%]
外部验证的卷积神经网络（CNN）人工智能模型在急诊头部CT扫描诊断测试中的准确性系统评价
Saana M Mäenpää,Miikka Korja
Saana M Mäenpää
Background: The surge in emergency head CT imaging and artificial intelligence (AI) advancements, especially deep learning (DL) and convolutional neural networks (CNN), have accelerated the development of computer-aided d...