DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network

Non-Insulin-Dependent Diabetes Mellitus (NIDDM) is a chronic health condition caused by high blood sugar levels, and if not treated early, it can lead to serious complications i.e. blindness. Human Activity Recognition (HAR) offers potential for early NIDDM diagnosis, emerging as a key application f...

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Veröffentlicht in:	Journal of big data Jg. 11; H. 1; S. 103 - 37
Hauptverfasser:	Alam, Md Nuho Ul, Hasnine, Ibrahim, Bahadur, Erfanul Hoque, Masum, Abdul Kadar Muhammad, Urbano, Mercedes Briones, Vergara, Manuel Masias, Uddin, Jia, Ashraf, Imran, Samad, Md. Abdus
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.12.2024 Springer Nature B.V SpringerOpen
Schlagworte:	Acknowledgment Activities of daily living Artificial neural networks Big Data Big Data and Artificial Intelligence in Emerging Scientific Fields Blindness Chronic illnesses Communications Engineering Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Database Management Diabetes Diabetes mellitus Diabetic retinopathy Diagnosis Diagnostic tests Graph Neural Network Graph neural networks Human activity recognition Humans Information Storage and Retrieval Insulin Mathematical Applications in Computer Science Medical diagnosis Networks Neural networks NIDDM Patients Recognition Research subjects Retinal images Retinopathy Risk factors Smartphones Symptoms Diabetic retinopathy Diabetes Human activity recognition Graph Neural Network NIDDM
ISSN:	2196-1115, 2196-1115
Online-Zugang:	Volltext
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