Using Temporal Features to Provide Data-Driven Clinical Early Warnings for Chronic Obstructive Pulmonary Disease and Asthma Care Management: Protocol for a Secondary Analysis

Both chronic obstructive pulmonary disease (COPD) and asthma incur heavy health care burdens. To support tailored preventive care for these 2 diseases, predictive modeling is widely used to give warnings and to identify patients for care management. However, 3 gaps exist in current modeling methods...

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Veröffentlicht in:	JMIR research protocols 2019-06, Vol.8 (6), p.e13783-e13783
Hauptverfasser:	Luo, Gang, Stone, Bryan L, Koebnick, Corinna, He, Shan, Au, David H, Sheng, Xiaoming, Murtaugh, Maureen A, Sward, Katherine A, Schatz, Michael, Zeiger, Robert S, Davidson, Giana H, Nkoy, Flory L
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Asthma Chronic obstructive pulmonary disease Costs Electronic health records Emergency medical care Health care expenditures Hospitalization Hospitals Machine learning Patients Protocol Risk factors Variables
Online-Zugang:	Volltext
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