Nianci Yao,Yonghong Wang,Zhiheng Liao et al.
Nianci Yao et al.
Consequently, five possible formation pathways of OOMs were identified using a machine learning approach combined with their diurnal patterns. Further analysis suggested that OOMs, together with sulfuric acid and ammonia, are highly involved in the formation of nanoparticles.
Identifying determinants of under-5 mortality in Bangladesh: A machine learning approach with BDHS 2022 data [0.03%]
基于BDHS 2022数据的机器学习方法识别孟加拉国5岁以下儿童死亡率的影响因素
Shayla Naznin,Md Jamal Uddin,Ahmad Kabir
Shayla Naznin
Background: Under-5 mortality in Bangladesh remains a critical indicator of public health and socio-economic development. Traditional methods often struggle to capture the complex, non-linear relationships influencing und...
A synthetic data-driven machine learning approach for athlete performance attenuation prediction [0.03%]
一种基于合成数据的机器学习运动员表现衰减预测方法
Mauricio C Cordeiro,Ciaran O Cathain,Lorcan Daly et al.
Mauricio C Cordeiro et al.
Introduction: Athlete performance monitoring is effective for optimizing training strategies and preventing injuries. However, applying machine learning (ML) frameworks to this domain remains challenging due to data scarc...
Electrocardiogram-based diagnosis of liver diseases: an externally validated and explainable machine learning approach [0.03%]
基于心电图的肝病诊断：一种外部验证且可解释的机器学习方法
Juan Miguel Lopez Alcaraz,Wilhelm Haverkamp,Nils Strodthoff
Juan Miguel Lopez Alcaraz
Background: Liver diseases present a significant global health challenge and often require costly, invasive diagnostics. Electrocardiography (ECG), a widely available and non-invasive tool, can enable the detection of liv...
Prediction of attention deficit hyperactivity disorder using the comprehensive attention test: a large-scale machine learning approach [0.03%]
基于综合注意力测试的大规模机器学习注意缺陷多动障碍预测模型研究
Kwang Su Cha,Bongseog Kim,Jun-Young Lee et al.
Kwang Su Cha et al.
Background: The diagnosis of attention deficit hyperactivity disorder (ADHD) relies on comprehensive approaches, including clinical interviews, scales, and neuropsychological assessments. However, the process is often lim...
Gray Matter Differences in Adolescent Psychiatric Inpatients: A Machine Learning Study of Bipolar Disorder and Other Psychopathologies [0.03%]
基于机器学习的精神病住院青少年灰质差异性研究：情感障碍及其他精神病理学状况下的比较分析
Renata Rozovsky,Maria Wolfe,Halimah Abdul-Waalee et al.
Renata Rozovsky et al.
We employed a whole-brain machine learning approach focusing on gray matter volumes (GMVs) to contribute to defining objective biomarkers of BD and discriminating it from other forms of psychopathology, including subthreshold manic presentations without a BD Type I/II diagnosis.
Clinical significance of risk factor analysis in pancreatic cancer by using supervised model of machine learning [0.03%]
机器学习监督模型在胰腺癌危险因素分析中的临床意义
Amir Sherchan,Feng Jin,Bhakti Sherchan et al.
Amir Sherchan et al.
This study aimed to identify clinically relevant predictors of pancreatic cancer using a supervised machine learning approach and to develop a risk stratification tool with diagnostic capabilities.
Research on residue detection of prohibited drugs in shrimp based on the thin-layer chromatography-surface-enhanced Raman spectroscopy combined method [0.03%]
基于薄层色谱-表面增强拉曼光谱联用的虾中违禁药物残留检测研究
Ailing Tan,Yunhao He,Haoyu Wang et al.
Ailing Tan et al.
A machine learning approach that combined principal component analysis with support vector regression was developed for quantification of the residues from their TLC-SERS spectra.
BanglaNewsClassifier: A machine learning approach for news classification in Bangla Newspapers using hybrid stacking classifiers [0.03%]
基于混合堆叠分类器的孟加拉语新闻分类的机器学习方法-BanglaNewsClassifier
Tanzir Hossain,Ar-Rafi Islam,Md Humaion Kabir Mehedi et al.
Tanzir Hossain et al.
Bangla news floods the web, and the need for smarter and more efficient classification techniques is greater than ever. Previous studies mostly focused on traditional models, overlooking the potential of hybrid techniques to handle the ever...
Cost-effectiveness of the 3E model in diabetes management: a machine learning approach to assess long-term economic impact [0.03%]
基于机器学习的3E模式在糖尿病管理中的成本效益分析及长期经济影响评估
Supriya Raghav,Santosh Kumar,Hamid Ashraf et al.
Supriya Raghav et al.
Background: This study investigated the cost-effectiveness and clinical impact of the 3E model (education, empowerment, and economy) in diabetes management using advanced machine learning techniques. ...
Observational Study
Frontiers in public health. 2025 May 23:13:1571546. DOI:10.3389/fpubh.2025.1571546 2025
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