Two-stage learning-based prediction of bronchopulmonary dysplasia in very low birth weight infants: a nationwide cohort study.

Hwang, Jae Kyoon; Kim, Dae Hyun; Na, Jae Yoon; Son, Joonhyuk; Oh, Yoon Ju; Jung, Donggoo; Kim, Chang-Ryul; Kim, Tae Hyun; Park, Hyun-Kyung

Hwang, Jae Kyoon; Kim, Dae Hyun; Na, Jae Yoon; Son, Joonhyuk; Oh, Yoon Ju; Jung, Donggoo; Kim, Chang-Ryul; Kim, Tae Hyun; Park, Hyun-Kyung.

Afiliación

Hwang JK; Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea.
Kim DH; Department of Artificial Intelligence, Hanyang University, Seoul, Republic of Korea.
Na JY; Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea.
Son J; Department of Pediatric Surgery, Hanyang University College of Medicine, Seoul, Republic of Korea.
Oh YJ; Department of Artificial Intelligence, Hanyang University, Seoul, Republic of Korea.
Jung D; Department of Artificial Intelligence, Hanyang University, Seoul, Republic of Korea.
Kim CR; Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea.
Kim TH; Department of Computer Science, Hanyang University, Seoul, Republic of Korea.
Park HK; Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea.

Front Pediatr ; 11: 1155921, 2023.

Article en En | MEDLINE | ID: mdl-37384307

Palabras clave

bronchopulmonary dysplasia (BPD); machine learningML; nationwide cohort; prediction; very low birth weight infants (VLBWI)

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Pediatr Año: 2023 Tipo del documento: Article

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