A radiomics and deep learning nomogram developed and validated for predicting no-collapse survival in patients with osteonecrosis after multiple drilling [0.03%]
基于影像组学和深度学习的股骨头坏死多孔术后不塌陷生存预测模型研究
Fan Liu,De-Bao Zhang,Shi-Huan Cheng et al.
Fan Liu et al.
Purpose: Identifying patients who may benefit from multiple drilling are crucial. Hence, the purpose of the study is to utilize radiomics and deep learning for predicting no-collapse survival in patients with femoral head...
Correction: Which criteria are important in usability evaluation of mHealth applications: an umbrella review [0.03%]
纠正：m健康应用程序的可用性评价哪些标准重要：一把伞审查
Zahra Galavi,Mahdieh Montazeri,Reza Khajouei
Zahra Galavi
FHIR PIT: a geospatial and spatiotemporal data integration pipeline to support subject-level clinical research [0.03%]
FHIR PIT：一个地理空间和时空数据集成管道，用于支持受试者水平的临床研究
Karamarie Fecho,Juan J Garcia,Hong Yi et al.
Karamarie Fecho et al.
Background: Environmental exposures such as airborne pollutant exposures and socio-economic indicators are increasingly recognized as important to consider when conducting clinical research using electronic health record ...
Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods [0.03%]
基于机器学习方法识别有效的免疫生物标志物以辅助脱发诊断
Qingde Zhou,Lan Lan,Wei Wang et al.
Qingde Zhou et al.
Background: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is not well understood, and there is no targeted therapy available for AA...
Predictive value of machine learning for the progression of gestational diabetes mellitus to type 2 diabetes: a systematic review and meta-analysis [0.03%]
机器学习预测妊娠期糖尿病进展为2型糖尿病的预测价值：系统回顾和meta分析
Meng Zhao,Zhixin Yao,Yan Zhang et al.
Meng Zhao et al.
Background: This systematic review aims to explore the early predictive value of machine learning (ML) models for the progression of gestational diabetes mellitus (GDM) to type 2 diabetes mellitus (T2DM). ...
%diag_test: a generic SAS macro for evaluating diagnostic accuracy measures for multiple diagnostic tests [0.03%]
诊断准确性评价的通用SAS宏诊断多个检验指标
Jacques K Muthusi,Peter W Young,Frankline O Mboya et al.
Jacques K Muthusi et al.
Background: Measures of diagnostic test accuracy provide evidence of how well a test correctly identifies or rules-out disease. Commonly used diagnostic accuracy measures (DAMs) include sensitivity and specificity, predic...
Natural language processing to identify suicidal ideation and anhedonia in major depressive disorder [0.03%]
自然语言处理在重度抑郁症患者自杀意念及快感缺失识别中的应用
L Alexander Vance,Leslie Way,Deepali Kulkarni et al.
L Alexander Vance et al.
Background: Anhedonia and suicidal ideation are symptoms of major depressive disorder (MDD) that are not regularly captured in structured scales but may be captured in unstructured clinical notes. Natural language process...
Mortality and morbidity patterns in Yaoundé, Cameroon: an ICD-11 classification-based analysis [0.03%]
基于ICD-11分类的雅温得市死亡和疾病模式分析
Georges Nguefack-Tsague,Fabrice Zobel Lekeumo Cheuyem,Boris Edmond Noah et al.
Georges Nguefack-Tsague et al.
Background: In Cameroon, like in many other resource-limited countries, data generated by health settings including morbidity and mortality parameters are not always uniform. In the absence of a national guideline necessa...
Human-centered design of a health recommender system for orthopaedic shoulder treatment [0.03%]
以人为本的健康推荐系统在骨科肩关节治疗中的设计
Akanksha Singh,Benjamin Schooley,John Mobley et al.
Akanksha Singh et al.
Background: Rich data on diverse patients and their treatments and outcomes within Electronic Health Record (EHR) systems can be used to generate real world evidence. A health recommender system (HRS) framework can be app...
An approach to boost adherence to self-data reporting in mHealth applications for users without specific health conditions [0.03%]
提高健康人群使用移动医疗应用程序自我报告数据依从性的方法研究
Maria Aguiar,Ander Cejudo,Gorka Epelde et al.
Maria Aguiar et al.
Background: The popularization of mobile health (mHealth) apps for public health or medical care purposes has transformed human life substantially, improving lifestyle behaviors and chronic condition management. The objec...