Integrating machine learning approach to identify sleep-disordered breathing in hypertrophic cardiomyopathy.

Rhee, Tae-Min; Kim, Hyung-Kwan

Rhee, Tae-Min; Kim, Hyung-Kwan.

Affiliation

Rhee TM; Division of Cardiology, Department of Internal Medicine, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea (the Republic of).
Kim HK; Division of Cardiology, Department of Internal Medicine, Seoul National University Hospital and Seoul National University College of Medicine, Seoul, Korea (the Republic of) cardiman73@gmail.com.

Heart ; 110(14): 931-932, 2024 Jun 25.

Article in En | MEDLINE | ID: mdl-38802128

Subject(s)

Cardiomyopathy, Hypertrophic; Machine Learning; Sleep Apnea Syndromes; Humans; Cardiomyopathy, Hypertrophic/complications; Cardiomyopathy, Hypertrophic/diagnosis; Cardiomyopathy, Hypertrophic/physiopathology; Sleep Apnea Syndromes/diagnosis; Sleep Apnea Syndromes/physiopathology; Sleep Apnea Syndromes/complications; Male; Female; Middle Aged; Polysomnography/methods

Key words

Cardiomyopathy, Hypertrophic

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Full text: 1 Database: MEDLINE Main subject: Sleep Apnea Syndromes / Cardiomyopathy, Hypertrophic / Machine Learning Limits: Female / Humans / Male / Middle aged Language: En Journal: Heart Journal subject: CARDIOLOGIA Year: 2024 Type: Article

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