Engaging individuals in digital health research panels: A qualitative study including participants in vulnerable positions [0.03%]
面向研究对象的数字健康研究小组：包括弱势群体成员的定性研究
Corine Oldhoff-Nuijsink,Mirjam P Fransen,Jeanine Suurmond et al.
Corine Oldhoff-Nuijsink et al.
Individuals in vulnerable circumstances often face challenges in accessing and utilizing digital health tools. They are also underrepresented in digital health research. Consequently, digital health tools may not be aligned with their speci...
Optimization of artificial intelligence models for prediction of new-onset cardiovascular disease in patients with arterial hypertension [0.03%]
针对动脉高血压患者新发心血管疾病的预测 人工智能模型的优化研究
Enrique Rodilla,Olast Arrizibita-Iriarte,Blanca Miranda-Serrano et al.
Enrique Rodilla et al.
Advanced preventive strategies are needed to decrease the burden of cardiovascular disease (CVD). We aimed to develop a predictive tool to identify individuals at higher CVD risk and facilitate proactive interventions to improve clinical ou...
Real-time prediction of cardiorespiratory deterioration during paediatric critical care transport using interpretable machine learning [0.03%]
基于可解释机器学习的儿科重症监护运输中心血管呼吸功能恶化的实时预测模型研究
Milan Kapur,Kezhi Li,Alexander Brown et al.
Milan Kapur et al.
Interhospital transport of critically ill children carries inherent risks, including unexpected respiratory and cardiovascular deterioration. Early warning of impending patient deterioration may allow physicians to intervene and prevent fur...
Explainable machine learning for predicting longitudinal dementia status: Establishing a leakage-free benchmark [0.03%]
一种用于预测纵向痴呆状态的可解释机器学习方法：建立无数据泄漏的标准模型
Mohammad Mahdi Ghiasi,Ryan Stanley Falck,Teresa Liu-Ambrose et al.
Mohammad Mahdi Ghiasi et al.
Dementia research often suffers from methodological pitfalls such as label-information and subject-information leakages. Leveraging the longitudinal OASIS-2 cohort, this study identifies and addresses three critical gaps in prior research: ...
Use of UK national health databases for detecting intra-cranial aneurysm rupture in the Risk of Aneurysm Rupture (ROAR) study [0.03%]
英国国家健康数据库在瘤样囊肿破裂检测中的应用——ROAR研究
Samuel Hall,Jacqueline Birks,Frederick Ewbank et al.
Samuel Hall et al.
The objective of this study was to determine the sensitivity of national databases for identifying aneurysm rupture events in patients with unruptured intracranial aneurysms and determine their suitability for follow-up for patients in the ...
Structure-aware retinal disentanglement reveals the genetic architecture of ocular and systemic diseases [0.03%]
基于视网膜结构的解缠方法揭示了眼部和系统性疾病的遗传结构
Chiyu Wei,Heping Zhang,Ruibin Huang et al.
Chiyu Wei et al.
Deep learning effectively extracts retinal phenotypes but often functions as an entangled black box, obscuring specific genetic mechanisms and hindering clinical interpretability. To resolve this, we present the Unsupervised Ophthalmic Feat...
Cross-spectral fusion of thermal and RGB imaging for objective pain estimation [0.03%]
基于热像和RGB图像的交叉谱融合用于客观疼痛评估
Oussama El Othmani,Sami Naouali
Oussama El Othmani
Pain assessment remains challenging for patients unable to verbally communicate, including neonates, cognitively impaired individuals, sedated patients, and those who suppress expressions due to cultural norms or stoicism. We demonstrate th...
Explainable AI in hospital clinical decision support systems: A scoping review of healthcare professionals' perspectives [0.03%]
可解释的人工智能在医院临床决策支持系统中的应用：医疗保健专业人员的视角的综述研究
Bethany A Van Dort,Thomas Engelsma,Pamela Sneekes et al.
Bethany A Van Dort et al.
Explainable Artificial Intelligence (XAI) has the potential to enhance clinical decision support (CDS) systems however, it remains unclear how XAI systems are perceived by healthcare professionals in hospital settings, and if new challenges...
Retinal biological age correlates with bone mineral density and fracture risk score and predicts incident osteoporosis [0.03%]
视网膜生物学年龄与骨矿密度、骨折风险评分相关，并可预测继发性骨质疏松症
Qingsheng Peng,Can Can Xue,Kenon Chua et al.
Qingsheng Peng et al.
Osteoporosis often lacks accessible screening tools, leading to underdiagnosis and increased fracture risk. We explored the potential of a retinal aging biomarker, measured by the RetiAGE algorithm, in stratifying osteoporosis risk. Cross-s...
Deep-learning time-series anomaly detection of acute kidney injury from creatinine-eGFR trajectories in the ICU [0.03%]
基于ICU中血清肌酐-eGFR轨迹的急性肾损伤的深度学习时间序列异常检测
Yoonjin Kang,Soojeong Yun,Seung Min Song et al.
Yoonjin Kang et al.
Acute kidney injury (AKI) is common in the intensive care unit (ICU), and fixed creatinine thresholds may miss clinically relevant dynamics. We tested whether a deep-learning anomaly signal from short creatinine-estimated glomerular filtrat...