AIMC Topic: Self Report

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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 Dec 7, 2020
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 ...
Humans Machine Learning Middle Aged Quality of Life Self Report Kidney Calculi Female Aged Adult Male
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Comparing supervised and unsupervised approaches to emotion categorization in the human brain, body, and subjective experience.

Scientific reports Nov 20, 2020
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...
Psychophysiology Grounded Theory Self Report Humans Psychology Brain Datasets as Topic Models, Psychological Magnetic Resonance Imaging Cluster Analysis Emotions Unsupervised Machine Learning Supervised Machine Learning
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Using Machine Learning to Predict Suicide Attempts in Military Personnel.

Psychiatry research Oct 22, 2020
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...
Cognitive Behavioral Therapy Follow-Up Studies Predictive Value of Tests Self Report Military Personnel Humans Machine Learning Female Adult Male Suicide, Attempted Suicidal Ideation
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Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment.

Human brain mapping Oct 8, 2020
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...
Humans Machine Learning Brain Aged Male Middle Aged Disease Progression Prognosis Retrospective Studies Female Educational Status Amnesia White Matter Neuropsychological Tests Diagnostic Self Evaluation Amygdala Cognitive Dysfunction Follow-Up Studies Magnetic Resonance Imaging Self Report
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Using Machine Learning and Smartphone and Smartwatch Data to Detect Emotional States and Transitions: Exploratory Study.

JMIR mHealth and uHealth Sep 29, 2020
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...
Smokers Machine Learning Smartphone Emotions Self Report Humans
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Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Scientific reports Jul 28, 2020
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...
Humans Confidence Intervals Motor Activity Smartphone Mass Screening Parkinson Disease Self Report Female Middle Aged Male Deep Learning Cohort Studies ROC Curve
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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 Jul 27, 2020
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., ...
Self Report Interpersonal Relations Humans Machine Learning Female Male Longitudinal Studies Family Characteristics
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Gait can reveal sleep quality with machine learning models.

PloS one Sep 25, 2019
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...
Self Report Healthy Volunteers Young Adult Humans Sleep Polysomnography Machine Learning Health Status Indicators Adult Female Male Gait
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Scoring colorectal cancer risk with an artificial neural network based on self-reportable personal health data.

PloS one Aug 22, 2019
Colorectal cancer (CRC) is third in prevalence and mortality among all cancers in the US. Currently, the United States Preventative Services Task Force (USPSTF) recommends anyone ages 50-75 and/or with a family history to be screened for CRC. To impr...
Male Cardiovascular Diseases Middle Aged Health Surveys Humans Models, Statistical United States Neural Networks, Computer Female Self Report Diabetes Mellitus Prognosis Risk Factors Practice Guidelines as Topic Health Status Aged Medical History Taking Early Detection of Cancer Colorectal Neoplasms
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Machine-Learning-Based Detection of Craving for Gaming Using Multimodal Physiological Signals: Validation of Test-Retest Reliability for Practical Use.

Sensors (Basel, Switzerland) Aug 9, 2019
Internet gaming disorder in adolescents and young adults has become an increasing public concern because of its high prevalence rate and potential risk of alteration of brain functions and organizations. Cue exposure therapy is designed for reducing ...
Electrooculography Video Games Craving Behavior, Addictive Saccades Male Self Report Heart Rate Respiratory Rate Humans Machine Learning Young Adult
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