Sample-Pair Envelope Diamond Autoencoder Ensemble Algorithm for Chronic Disease Recognition

Chronic diseases are severe and life-threatening, and their accurate early diagnosis is difficult. Machine-learning-based processes of data collected from the human body using wearable sensors are a valid method currently usable for diagnosis. However, it is difficult for wearable sensor systems to...

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Veröffentlicht in:	Applied sciences Jg. 13; H. 12; S. 7322
Hauptverfasser:	Zhang, Yi, Ma, Jie, Qin, Xiaolin, Li, Yongming, Zhang, Zuwei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.06.2023
Schlagworte:	Accuracy Algorithms Cardiovascular disease Chronic diseases Chronic illnesses Decision trees Deep learning diamond-like feature learning Discriminant analysis envelope learning Feature selection feature-embedded stacked sparse autoencoder Machine learning Neural networks Physiology recognition of chronic disease sample-pair envelope concatenation Sensors Type 2 diabetes wearable sensor monitoring China
ISSN:	2076-3417, 2076-3417
Online-Zugang:	Volltext
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