Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011–2018

The association of depression with use of prescription drugs in adults with noncommunicable diseases: Based on NHANES in 2005–2016

(2021) Huixin Yang et al.   JOURNAL OF AFFECTIVE DISORDERS

An empirical survey of data augmentation for time series classification with neural networks

(2021) Brian Kenji Iwana et al.   PLoS One

Quantitative structure–property relationships for the calculation of the soil adsorption coefficient using machine learning algorithms with calculated chemical properties from open-source software

(2020) Yoshiyuki Kobayashi et al.   ENVIRONMENTAL RESEARCH

Theories of Error Back-Propagation in the Brain

(2019) James C.R. Whittington et al.   TRENDS IN COGNITIVE SCIENCES

A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models

(2019) Evangelia Christodoulou et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Random forest, support vector machine, and neural networks to modelling suspended sediment in Tigris River-Baghdad

(2019) Mustafa Al-Mukhtar   ENVIRONMENTAL MONITORING AND ASSESSMENT

Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm

(2019) Jihoon Oh et al.   JOURNAL OF AFFECTIVE DISORDERS

Trends in depression among Adults in the United States, NHANES 2005–2016

(2019) Binbin Yu et al.   JOURNAL OF AFFECTIVE DISORDERS

SGB-ELM: An Advanced Stochastic Gradient Boosting-Based Ensemble Scheme for Extreme Learning Machine

(2018) Hua Guo et al.   Computational Intelligence and Neuroscience

Correlation Analysis to Identify the Effective Data in Machine Learning: Prediction of Depressive Disorder and Emotion States

(2018) Sunil Kumar et al.   International Journal of Environmental Research and Public Health

Application of Machine Learning Techniques for Clinical Predictive Modeling: A Cross-Sectional Study on Nonalcoholic Fatty Liver Disease in China

(2018) Han Ma et al.   Biomed Research International

Trajectories of Depressive Symptoms Before Diagnosis of Dementia

(2017) Archana Singh-Manoux et al.   JAMA Psychiatry

Machine Learning and Data Mining Methods in Diabetes Research

(2017) Ioannis Kavakiotis et al.   Computational and Structural Biotechnology Journal

Social Support and Health Service Use in Depressed Adults: Findings From the National Health and Nutrition Examination Survey

(2016) Sarah B. Andrea et al.   GENERAL HOSPITAL PSYCHIATRY

Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports

(2016) R C Kessler et al.   MOLECULAR PSYCHIATRY

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

(2016) Joanna F. Dipnall et al.   PLoS One

SLEEP DURATION AND DEPRESSION AMONG ADULTS: A META-ANALYSIS OF PROSPECTIVE STUDIES

(2015) Long Zhai et al.   DEPRESSION AND ANXIETY

A Mobile Health Application to Predict Postpartum Depression Based on Machine Learning

(2015) Santiago Jiménez-Serrano et al.   Telemedicine and e-Health

Investigation of the Relationship between Increased Vertical Overlap with Minimum Horizontal Overlap and the Signs of Temporomandibular Disorders

(2015) Neslihan Tinastepe et al.   Journal of Prosthodontics-Implant Esthetic and Reconstructive Dentistry

A Mobile Health Application to Predict Postpartum Depression Based on Machine Learning

(2015) Santiago Jiménez-Serrano et al.   Telemedicine and e-Health

Mental health: A world of depression

(2014) Kerri Smith   NATURE

The Relationship between Postpartum Depression and Breastfeeding

(2012) Aisha Hamdan et al.   INTERNATIONAL JOURNAL OF PSYCHIATRY IN MEDICINE

The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: a systematic review

(2010) Kurt Kroenke et al.   GENERAL HOSPITAL PSYCHIATRY