Last Posted: Jun 28, 2022
- Barriers of artificial intelligence implementation in the diagnosis of obstructive sleep apnea.
Brennan Hannah L et al. Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale 2022 51(1) 16
- Six-month sequelae of post-vaccination SARS-CoV-2 infection: a retrospective cohort study of 10,024 breakthrough infections.
Taquet Maxime, et al. Brain, behavior, and immunity 2022 0 0.
- Study on Adherence to Positive Airway Pressure Treatment for Patients with Obstructive Sleep Apnea Using Real-world Big Data in a Telemedicine Management System.
Yi Huijie et al. Methods (San Diego, Calif.) 2022
- Genetic heterogeneity on sleep disorders in Parkinson's disease: a systematic review and meta-analysis.
Huang Jingxuan et al. Translational neurodegeneration 2022 11(1) 21
- Trends of Internet Search Volumes for Major Depressive Disorder Symptoms During the COVID-19 Pandemic in Korea: An Interrupted Time-Series Analysis.
Kim Jieun, et al. Journal of Korean medical science 2022 0 0. (14) e108
- Diagnosis of Sleep Apnoea Using a Mandibular Monitor and Machine Learning Analysis: One-Night Agreement Compared to in-Home Polysomnography.
Kelly Julia L et al. Frontiers in neuroscience 2022 16726880
- A distinctive profile of family genetic risk scores in a Swedish national sample of cases of fibromyalgia, irritable bowel syndrome, and chronic fatigue syndrome compared to rheumatoid arthritis and major depression.
Kendler Kenneth S et al. Psychological medicine 2022 1-8
- 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
- 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
- Clinical applications of artificial intelligence in sleep medicine: a sleep clinician's perspective.
Bandyopadhyay Anuja et al. Sleep & breathing = Schlaf & Atmung 2022
HLBS-PopOmics is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other materials that address the translation of genomic and other precision health discoveries into improved health care and prevention related to Heart and Vascular Diseases(H), Lung Diseases(L), Blood Diseases(B), and Sleep Disorders(S)...more
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Mensah GA, Yu W, Barfield WL, Clyne M, Engelgau MM, Khoury MJ. HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders. Genet Med. 2018 Sep 10. doi: 10.1038/s41436-018-0118-1
Disclaimer: Articles listed in the Public Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.