Digital-based emergency prevention and control system: enhancing infection control in psychiatric hospitals [0.03%]
基于数字的紧急预防和控制系统——提高精神病医院感染控制能力
Mi Yang,Xiaojun Zhu,Fei Yan et al.
Mi Yang et al.
Background: The practical application of infectious disease emergency plans in mental health institutions during the ongoing pandemic has revealed significant shortcomings. These manifest as chaotic management of mental h...
External validation of AI-based scoring systems in the ICU: a systematic review and meta-analysis [0.03%]
重症监护病房中基于人工智能的评分系统外部验证的系统评价和meta分析
Patrick Rockenschaub,Ela Marie Akay,Benjamin Gregory Carlisle et al.
Patrick Rockenschaub et al.
Background: Machine learning (ML) is increasingly used to predict clinical deterioration in intensive care unit (ICU) patients through scoring systems. Although promising, such algorithms often overfit their training coho...
Predicting Gestational Diabetes Mellitus in the first trimester using machine learning algorithms: a cross-sectional study at a hospital fertility health center in Iran [0.03%]
基于机器学习算法预测伊朗某医院生殖健康中心孕妇妊娠期糖尿病的一项横断面研究
Somayeh Kianian Bigdeli,Marjan Ghazisaedi,Seyed Mohammad Ayyoubzadeh et al.
Somayeh Kianian Bigdeli et al.
Background: Gestational Diabetes Mellitus (GDM) is a common complication during pregnancy. Late diagnosis can have significant implications for both the mother and the fetus. This research aims to create an early predicti...
Correction: Development and validation of a nomogram model for prolonged length of stay in spinal fusion patients: a retrospective analysis [0.03%]
纠正：脊柱融合患者住院时间延长的预测模型的建立和验证：一项回顾性分析
Linghong Wu,Xiaozhong Peng,Yao Lu et al.
Linghong Wu et al.
Effect of short message service reminders in improving optimal antenatal care, skilled birth attendance and postnatal care in low-and middle-income countries: a systematic review and meta-analysis [0.03%]
短信提醒对改善低收入和中等收入国家的最佳产前护理、技能接生员接生和产后护理的影响：系统评价和meta分析
Tesfahun Hailemariam,Asmamaw Atnafu,Lemma Derseh Gezie et al.
Tesfahun Hailemariam et al.
Background: Digital health has emerged as a promising solution for enhancing health system in the recent years, showing significant potential in improving service outcomes, particularly in low and middle-income countries ...
Does the FNA sperm retrieval failure prediction model work well for current NOA individuals undertaking risk screening before the operation? Model validation, high-risk population identification and potential alternative sperm retrieval exploration [0.03%]
FNA取精失败预测模型用于当前NOA人群术前风险筛查是否有效？——模型验证、高危人群识别及潜在替代取精路径探索
Xiaohui Jiang,Dingming Li,Yi Zheng et al.
Xiaohui Jiang et al.
Background: Non-obstructive azoospermia (NOA), the severe type of male infertility. The objective of this study was to evaluate the predictive accuracy of a prediction model of sperm retrieval failure with fine needle asp...
A new risk assessment model of venous thromboembolism by considering fuzzy population [0.03%]
考虑模糊人口的新型静脉血栓栓塞风险评估模型
Xin Wang,Yu-Qing Yang,Xin-Yu Hong et al.
Xin Wang et al.
Background: Inpatients with high risk of venous thromboembolism (VTE) usually face serious threats to their health and economic conditions. Many studies using machine learning (ML) models to predict VTE risk overlook the ...
Determining the minimum data elements to develop a child malnutrition registry system [0.03%]
确定建立儿童营养不良登记系统的最小数据元素
Malihe Sadeghi,Mostafa Langarizadeh,Beheshteh Olang et al.
Malihe Sadeghi et al.
Background: Today, malnutrition is one of the biggest health crises for children in the world. Access to accurate and high-quality data is very important to establish policies to deal with it. Registries are considered va...
Autonomous detection of nail disorders using a hybrid capsule CNN: a novel deep learning approach for early diagnosis [0.03%]
一种新型深度学习方法：使用混合胶囊CNN自主检测指甲疾病以实现早期诊断
Gunjan Shandilya,Sheifali Gupta,Salil Bharany et al.
Gunjan Shandilya et al.
Major underlying health issues can be indicated by even minor nail infections. Subungual Melanoma is one of the most severe kinds since it is identified at a much later stage than other conditions. The purpose of this research is to offer n...
An improved electrocardiogram arrhythmia classification performance with feature optimization [0.03%]
基于特征优化的心电图心律失常分类性能提升方法研究
Annisa Darmawahyuni,Siti Nurmaini,Bambang Tutuko et al.
Annisa Darmawahyuni et al.
Background: Automatic classification of arrhythmias based on electrocardiography (ECG) data faces several significant challenges, particularly due to the substantial volume of clinical data involved in ECG signal analysis...