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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Heart, Lung, Blood and Sleep Disorders
Last data update: Apr 25, 2024
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Insomnia[original query]>>Original Studies[Product Type]
Major Depressive Disorder Prediction Based on Sleep-Wake Disorders Symptoms in US Adolescents: A Machine Learning Approach from National Sleep Research Resource.
Jingsong Luo et al. Psychol Res Behav Manag 2024 17691-703
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Automatic Detection of Chronic Insomnia from Polysomnographic and Clinical Variables Using Machine Learning.
Umaer Hanif et al. Annu Int Conf IEEE Eng Med Biol Soc 2023 20231-5
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General v. specific vulnerabilities: polygenic risk scores and higher-order psychopathology dimensions in the Adolescent Brain Cognitive Development (ABCD) Study.
Monika A Waszczuk et al. Psychol Med 2023 53(5) 1937-1946
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Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study.
Gerard Anmella et al. JMIR mHealth and uHealth 2023
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Initial antidepressant choice by non-psychiatrists: Learning from large-scale electronic health records.
Yi-Han Sheu et al. General hospital psychiatry 2023 8122-31
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Sleep disturbance as a transdiagnostic marker of psychiatric risk in children with neurodevelopmental risk genetic conditions.
Chawner Samuel J R A et al. Translational psychiatry 2023 13(1) 7
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Causal Association of Cardiovascular Risk Factors and Lifestyle Behaviors With Peripheral Artery Disease: A Mendelian Randomization Approach.
Hoek Anna G et al. Journal of the American Heart Association 2022 e025644
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Estimation of the number of inherited prion disease mutation carriers in the UK.
Corbie Rosie et al. European journal of human genetics : EJHG 2022
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Using machine learning to predict health-related quality of life outcomes in patients with low grade glioma, meningioma, and acoustic neuroma.
Karri Roshan et al. PloS one 2022 17(5) e0267931
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Burden of disease, treatment utilization, and the impact on education and employment in patients with sickle cell disease: A comparative analysis of high- and low- to middle-income countries for the international Sickle Cell World Assessment Survey (SWAY).
Osunkwo Ifeyinwa et al. American journal of hematology 2022
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Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study.
Wang Alex et al. JMIR mental health 2022 9(3) e35253
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Predicting non-response to multimodal day clinic treatment in severely impaired depressed patients: a machine learning approach.
Vetter Johannes Simon et al. Scientific reports 2022 12(1) 5455
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Comorbid insomnia among breast cancer survivors and its prediction using machine learning: a nationwide study in Japan.
Ueno Taro et al. Japanese journal of clinical oncology 2021
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Exploratory Data Mining Techniques (Decision Tree Models) for Examining the Impact of Internet-Based Cognitive Behavioral Therapy for Tinnitus: Machine Learning Approach.
Rodrigo Hansapani et al. Journal of medical Internet research 2021 23(11) e28999
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Factors to improve distress and fatigue in Cancer survivorship; further understanding through text analysis of interviews by machine learning.
Yang Kyungmi et al. BMC cancer 2021 21(1) 741
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Use of a Consultation Service Following Pharmacogenomic Testing in Psychiatry.
Dowd Daniel et al. CNS spectrums 2021 26(2) 179-180
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Pharmacogenetic Associations Between Atazanavir/UGT1A1*28 and Efavirenz/rs3745274 (CYP2B6) Account for Specific Adverse Reactions in Chilean Patients Undergoing Antiretroviral Therapy.
Poblete Daniela et al. Frontiers in pharmacology 2021 12660965
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Health impact of acute intermittent porphyria in latent and non-recurrent attacks patients.
Buendía-Martínez Juan et al. Orphanet journal of rare diseases 2021 16(1) 106
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A machine learning approach predicts future risk to suicidal ideation from social media data.
Roy Arunima et al. NPJ digital medicine 2020 May 3(1) 78
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Enhancing behavioral sleep care with digital technology: study protocol for a hybrid type 3 implementation-effectiveness randomized trial.
Germain Anne et al. Trials 2021 Jan 22(1) 46
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Developing a Process for the Analysis of User Journeys and the Prediction of Dropout in Digital Health Interventions: Machine Learning Approach.
Bremer Vincent et al. Journal of medical Internet research 2020 Oct 22(10) e17738
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Dissecting the Association Between Inflammation, Metabolic Dysregulation, and Specific Depressive Symptoms: A Genetic Correlation and 2-Sample Mendelian Randomization Study.
Kappelmann Nils et al. JAMA psychiatry 2020 Oct
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Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.
Irving Jessica et al. Schizophrenia bulletin 2020 Oct
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An atlas on risk factors for type 2 diabetes: a wide-angled Mendelian randomisation study.
Yuan Shuai et al. Diabetologia 2020 Sep
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A machine learning approach predicts future risk to suicidal ideation from social media data.
Roy Arunima et al. NPJ digital medicine 2020 378
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Clustering Insomnia Patterns by Data From Wearable Devices: Algorithm Development and Validation Study.
Park Sungkyu et al. JMIR mHealth and uHealth 2019 Dec 7(12) e14473
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A major role for common genetic variation in anxiety disorders.
Purves Kirstin L et al. Molecular psychiatry 2019 Nov
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Gender based differences, pharmacogenetics and adverse events in chronic pain management.
Planelles Beatriz et al. The pharmacogenomics journal 2019 Nov
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Computer Algorithms in Assessment of Obstructive Sleep Apnoea Syndrome and Its Application in Estimating Prevalence of Sleep Related Disorders in Population.
Katyayan Angira et al. Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India 2019 Sep 71(3) 352-359
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Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes.
Wang Heming, et al. Nature communications 2019 8 0. (1) 3503
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 25, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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