Interpretable machine-learning model for Predicting the Convalescent COVID-19 patients with pulmonary diffusing capacity impairment.

Ma, Fu-Qiang; He, Cong; Yang, Hao-Ran; Hu, Zuo-Wei; Mao, He-Rong; Fan, Cun-Yu; Qi, Yu; Zhang, Ji-Xian; Xu, Bo

Ma, Fu-Qiang; He, Cong; Yang, Hao-Ran; Hu, Zuo-Wei; Mao, He-Rong; Fan, Cun-Yu; Qi, Yu; Zhang, Ji-Xian; Xu, Bo.

Affiliation

Ma FQ; Hubei University of Chinese Medicine, Wuhan, 430065, China.
He C; Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan, 430061, China.
Yang HR; Affiliated Hospital of Hubei University of Traditional Chinese Medicine, Wuhan, 430061, China.
Hu ZW; Hubei Province Academy of Traditional Chinese Medicine, Wuhan, 430074, China.
Mao HR; School of Software, HuaZhong University of Science and Technology, Wuhan, 430074, China.
Fan CY; Wuhan No.1 Hospital, Wuhan, 430022, China.
Qi Y; Hubei University of Chinese Medicine, Wuhan, 430065, China.
Zhang JX; Hubei Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Wuhan, 430015, China.
Xu B; Hubei University of Chinese Medicine, Wuhan, 430065, China.

BMC Med Inform Decis Mak ; 23(1): 169, 2023 08 29.

Article in En | MEDLINE | ID: mdl-37644543

Subject(s)

COVID-19; Pulmonary Diffusing Capacity; Humans; Female; Middle Aged; Male; Follow-Up Studies; Area Under Curve; Machine Learning

Key words

COVID-19; Interpretable artificial intelligence; Machine learning; Maximal voluntary ventilation; Pulmonary diffusing capacity impairment

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pulmonary Diffusing Capacity / COVID-19 Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Male / Middle aged Language: En Journal: BMC Med Inform Decis Mak Journal subject: INFORMATICA MEDICA Year: 2023 Type: Article Affiliation country: China

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