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A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data
M Lee, T Park, JY Shin, M Park - Scientific Reports, 2024 - nature.com
Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic
abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced …
abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced …
Machine learning in the detection of dental cyst, tumor, and abscess lesions
Abstract Background and Objective Dental panoramic radiographs are utilized in computer-
aided image analysis, which detects abnormal tissue masses by analyzing the produced …
aided image analysis, which detects abnormal tissue masses by analyzing the produced …
An intelligent deep feature based metabolism syndrome prediction system for sleep disorder diseases
PR Anisha, C Kishor Kumar Reddy… - Multimedia Tools and …, 2024 - Springer
Abstract The Obstructive Sleep Apnea (OSA) analysis and prediction is the hottest topic in
the medical healthcare industry. However, identifying the sleep disorder and its Severity is …
the medical healthcare industry. However, identifying the sleep disorder and its Severity is …
Unsupervised clustering of longitudinal clinical measurements in electronic health records
Longitudinal electronic health records (EHR) can be utilized to identify patterns of disease
development and progression in real-world settings. Unsupervised temporal matching …
development and progression in real-world settings. Unsupervised temporal matching …
Explainable machine learning approach for hepatitis C diagnosis using SFS feature selection
Hepatitis C is a significant public health concern, resulting in substantial morbidity and
mortality worldwide. Early diagnosis and effective treatment are essential to prevent the …
mortality worldwide. Early diagnosis and effective treatment are essential to prevent the …
[HTML][HTML] Automated machine learning to develop predictive models of metabolic syndrome in patients with periodontal disease
Metabolic syndrome is experiencing a concerning and escalating rise in prevalence today.
The link between metabolic syndrome and periodontal disease is a highly relevant area of …
The link between metabolic syndrome and periodontal disease is a highly relevant area of …
[HTML][HTML] Metabolic Syndrome in the Amazon: Customizing Diagnostic Methods for Urban Communities
Background/Objectives: Metabolic syndrome is a significant public health issue, particularly
in urbanizing regions like the Peruvian Amazon, where lifestyle changes have increased the …
in urbanizing regions like the Peruvian Amazon, where lifestyle changes have increased the …
Predicting metabolic syndrome: Machine learning techniques for improved preventive medicine
O Goldman, O Ben-Assuli, S Ababa… - Health Informatics …, 2025 - journals.sagepub.com
Objectives: Metabolic syndrome (MetS) has a significant impact on health. MetS is the
umbrella term for a group of interdependent metabolic threats that contribute to the …
umbrella term for a group of interdependent metabolic threats that contribute to the …
Heart disease detection using machine learning
M Al-Habahbeh, M Alomari, H Khattab… - Bulletin of Electrical …, 2025 - beei.org
Heart disease continues to be a major worldwide health issue, requiring accurate prediction
models to improve early identification and treatment. This research aims to address two …
models to improve early identification and treatment. This research aims to address two …
Prediction of metabolic syndrome following a first pregnancy
Background The prevalence of metabolic syndrome is rapidly increasing in the United
States. We hypothesized that prediction models using data obtained during pregnancy can …
States. We hypothesized that prediction models using data obtained during pregnancy can …