Machine learning-based predictive modeling of depression in hypertensive populations
We aimed to develop prediction models for depression among US adults with hypertension
using various machine learning (ML) approaches. Moreover, we analyzed the mechanisms …
using various machine learning (ML) approaches. Moreover, we analyzed the mechanisms …
Development and validation of a depression risk prediction nomogram for US Adults with hypertension, based on NHANES 2007–2018
Y Wang, Y Zhang, B Ni, Y Jiang, Y Ouyang - Plos one, 2023 - journals.plos.org
Depression is of increasing concern as its prevalence increases. Our study's objective was
to create and evaluate a nomogram to predict the likelihood that hypertension patients may …
to create and evaluate a nomogram to predict the likelihood that hypertension patients may …
Predictive markers of depression in hypertension
Hypertension and depression, as 2 major public health issues, are closely related. For
patients having hypertension, in particular, depression is a risk factor for mortality and …
patients having hypertension, in particular, depression is a risk factor for mortality and …
[HTML][HTML] An in-depth analysis of machine learning approaches to predict depression
Among all the forms of psychological and mental disorders, depression is the most common
form. Nowadays a large number of youths and adults around the world suffer from …
form. Nowadays a large number of youths and adults around the world suffer from …
Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011–2018
C Zhang, X Chen, S Wang, J Hu, C Wang, X Liu - Psychiatry Research, 2021 - Elsevier
Depression is one of the most common mental health problems in middle-aged and elderly
people. The establishment of risk factor-based depression risk assessment model is …
people. The establishment of risk factor-based depression risk assessment model is …
Machine learning approaches for predicting hypertension and its associated factors using population-level data from three South Asian countries
Background Hypertension is the most common modifiable risk factor for cardiovascular
diseases in South Asia. Machine learning (ML) models have been shown to outperform …
diseases in South Asia. Machine learning (ML) models have been shown to outperform …
Prediction and diagnosis of depression using machine learning with electronic health records data: a systematic review
Background Depression is one of the most significant health conditions in personal, social,
and economic impact. The aim of this review is to summarize existing literature in which …
and economic impact. The aim of this review is to summarize existing literature in which …
Comparison of the performance of machine learning-based algorithms for predicting depression and anxiety among University Students in Bangladesh: A result of the …
MIH Nayan, MSG Uddin, MI Hossain… - Asian Journal of …, 2022 - journals.lww.com
Methods: A structured questionnaire-based online survey was conducted on 2121 university
students (private and public) living in Bangladesh. After obtaining informed consent, the …
students (private and public) living in Bangladesh. After obtaining informed consent, the …
[HTML][HTML] Use of machine learning approach to predict depression in the elderly in China: a longitudinal study
Background Early detection of potential depression among elderly people is conducive for
timely preventive intervention and clinical care to improve quality of life. Therefore …
timely preventive intervention and clinical care to improve quality of life. Therefore …
A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population
MZI Chowdhury, AA Leung, RL Walker, KC Sikdar… - Scientific Reports, 2023 - nature.com
Risk prediction models are frequently used to identify individuals at risk of developing
hypertension. This study evaluates different machine learning algorithms and compares …
hypertension. This study evaluates different machine learning algorithms and compares …