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Self Report

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Gait can reveal sleep quality with machine learning models.

PloS one
Sleep quality is an important health indicator, and the current measurements of sleep rely on questionnaires, polysomnography, etc., which are intrusive, expensive or time consuming. Therefore, a more nonintrusive, inexpensive and convenient method n...

What health records data are required for accurate prediction of suicidal behavior?

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.

Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Scientific reports
Fine-motor impairment (FMI) is progressively expressed in early Parkinson's Disease (PD) patients and is now known to be evident in the immediate prodromal stage of the condition. The clinical techniques for detecting FMI may not be robust enough and...

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies.

Proceedings of the National Academy of Sciences of the United States of America
Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., ...

Using Machine Learning and Smartphone and Smartwatch Data to Detect Emotional States and Transitions: Exploratory Study.

JMIR mHealth and uHealth
BACKGROUND: Emotional state in everyday life is an essential indicator of health and well-being. However, daily assessment of emotional states largely depends on active self-reports, which are often inconvenient and prone to incomplete information. A...

Using Machine Learning to Predict Suicide Attempts in Military Personnel.

Psychiatry research
Identifying predictors of suicide attempts is critical in intervention and prevention efforts, yet finding predictors has proven difficult due to the low base rate and underpowered statistical approaches. The objective of the current study was to use...

Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment.

Human brain mapping
Subjective cognitive decline (SCD) is a high-risk yet less understood status before developing Alzheimer's disease (AD). This work included 76 SCD individuals with two (baseline and 7 years later) neuropsychological evaluations and a baseline T1-weig...

Comparing supervised and unsupervised approaches to emotion categorization in the human brain, body, and subjective experience.

Scientific reports
Machine learning methods provide powerful tools to map physical measurements to scientific categories. But are such methods suitable for discovering the ground truth about psychological categories? We use the science of emotion as a test case to expl...

Estimating the health-related quality of life of kidney stone patients: initial results from the Wisconsin Stone Quality of Life Machine-Learning Algorithm (WISQOL-MLA).

BJU international
OBJECTIVE: To build the Wisconsin Stone Quality of Life Machine-Learning Algorithm (WISQOL-MLA) to predict urolithiasis patients' health-related quality of life (HRQoL) based on demographic, symptomatic and clinical data collected for the validation ...

Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set.

Journal of medical Internet research
BACKGROUND: In the United States, the rapidly evolving COVID-19 outbreak, the shortage of available testing, and the delay of test results present challenges for actively monitoring its spread based on testing alone.