Digital phenotyping of sleep patterns among heterogenous samples of Latinx adults using unsupervised learning.
Sign Up to like & getrecommendations! Published in 2021 at "Sleep medicine"
DOI: 10.1016/j.sleep.2021.07.023
Abstract: OBJECTIVE This study aimed to identify sleep disturbance subtypes ("phenotypes") among Latinx adults based on objective sleep data using a flexible unsupervised machine learning technique. METHODS This study was an analysis of sleep data from… read more here.
Keywords: digital phenotyping; phenotyping sleep; using unsupervised; latinx adults ... See more keywords
Using unsupervised learning to investigate injury-associated factors of animal-vehicle crashes
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Injury Control and Safety Promotion"
DOI: 10.1080/17457300.2022.2125532
Abstract: Abstract Animal vehicle crash is a critical yet often under-emphasized safety concern of Louisiana. During 2014-2018, over 14,000 animal-related crashes cost Louisiana more than $520 million. To identify multiple key contributing factors and their association… read more here.
Keywords: vehicle crashes; using unsupervised; animal vehicle; vehicle ... See more keywords
BIA: Behavior Identification Algorithm Using Unsupervised Learning Based on Sensor Data for Home Elderly
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2019.2943391
Abstract: Behavior identification plays an important role in supporting homecare for the elderly living alone. In literature, plenty of algorithms have been designed to identify behaviors of the elderly by learning features or extracting patterns from… read more here.
Keywords: behavior identification; identification algorithm; sensor data; using unsupervised ... See more keywords
Acoustic animal identification using unsupervised learning
Sign Up to like & getrecommendations! Published in 2023 at "Methods in Ecology and Evolution"
DOI: 10.1111/2041-210x.14103
Abstract: Passive acoustic monitoring is usually presented as a complementary approach to monitoring wildlife communities and assessing ecosystem conditions. Automatic species detection methods support biodiversity monitoring and analysis by providing information on the presence–absence of species,… read more here.
Keywords: methodology; using unsupervised; acoustic animal; biodiversity ... See more keywords
Uncovering psychiatric phenotypes using unsupervised machine learning: A data-driven symptoms approach
Sign Up to like & getrecommendations! Published in 2023 at "European Psychiatry"
DOI: 10.1192/j.eurpsy.2023.13
Abstract: Abstract Background Current categorical classification systems of psychiatric diagnoses lead to heterogeneity of symptoms within disorders and common co-occurrence of disorders. We investigated the heterogeneous and overlapping nature of symptom endorsement in a population-based sample… read more here.
Keywords: psychiatric phenotypes; using unsupervised; unsupervised machine; machine learning ... See more keywords
Identification of Subphenotypes of Opioid Use Disorder Using Unsupervised Machine Learning.
Sign Up to like & getrecommendations! Published in 2023 at "Studies in health technology and informatics"
DOI: 10.3233/shti230299
Abstract: This paper aimed to detect the latent clusters of patients with opioid use disorder and to identify the risk factors affecting drug misuse using unsupervised machine learning. The cluster with the highest proportion of successful… read more here.
Keywords: using unsupervised; unsupervised machine; machine learning; opioid use ... See more keywords
Using an Unsupervised Clustering Model to Detect the Early Spread of SARS-CoV-2 Worldwide
Sign Up to like & getrecommendations! Published in 2022 at "Genes"
DOI: 10.3390/genes13040648
Abstract: Deciphering the population structure of SARS-CoV-2 is critical to inform public health management and reduce the risk of future dissemination. With the continuous accruing of SARS-CoV-2 genomes worldwide, discovering an effective way to group these… read more here.
Keywords: unsupervised clustering; using unsupervised; sars cov; population ... See more keywords
Longitudinal profile of routine biomarkers for mortality prediction using unsupervised clustering algorithm in severely burned patients: a retrospective cohort study with prospectively collected data
Sign Up to like & getrecommendations! Published in 2023 at "Annals of Surgical Treatment and Research"
DOI: 10.4174/astr.2023.104.2.126
Abstract: Purpose Burn injury has high clinical heterogeneity and worse prognosis in severely burned patients. Clustering algorithms using unsupervised methods to identify groups with similar trajectories in heterogeneous disease patients can provide insight into mechanisms of… read more here.
Keywords: severely burned; using unsupervised; mortality prediction; mortality ... See more keywords