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Machine learning and deep learning predictive models for type 2 diabetes: a systematic review
Diabetes Mellitus is a severe, chronic disease that occurs when blood glucose levels rise
above certain limits. Over the last years, machine and deep learning techniques have been …
above certain limits. Over the last years, machine and deep learning techniques have been …
Machine learning for diabetes clinical decision support: a review
Type 2 diabetes has recently acquired the status of an epidemic silent killer, though it is non-
communicable. There are two main reasons behind this perception of the disease. First, a …
communicable. There are two main reasons behind this perception of the disease. First, a …
[HTML][HTML] Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective
Abstract Background and Objective Diabetes mellitus is a metabolic disorder characterized
by hyperglycemia, which results from the inadequacy of the body to secrete and respond to …
by hyperglycemia, which results from the inadequacy of the body to secrete and respond to …
Predictive modeling and analytics for diabetes using hyperparameter tuned machine learning techniques
SC Gupta, N Goel - Procedia Computer Science, 2023 - Elsevier
Accuracy of a classifier is important for the success of any prediction model. The more
accuracy a classifier possesses, the more robust the system is made on it. In this paper, a …
accuracy a classifier possesses, the more robust the system is made on it. In this paper, a …
[HTML][HTML] Stacking ensemble approach to diagnosing the disease of diabetes
A Daza, CFP Sánchez, G Apaza-Perez, J Pinto… - Informatics in Medicine …, 2024 - Elsevier
Background Diabetes is a very common disease today and has acquired a worrying focus in
the field of public health globally, in fact, it is estimated that the number of people with …
the field of public health globally, in fact, it is estimated that the number of people with …
Median-KNN Regressor-SMOTE-Tomek links for handling missing and imbalanced data in air quality prediction
The Air Quality Index (AQI) dataset contains information on measurements of pollutants and
ambient air quality conditions at certain location that can be used to predict air quality …
ambient air quality conditions at certain location that can be used to predict air quality …
Learning from imbalanced data in healthcare: State-of-the-art and research challenges
Datasets associated with medical and healthcare domains are imbalanced in nature. An
imbalanced dataset refers to a classification dataset where the number of instances of a …
imbalanced dataset refers to a classification dataset where the number of instances of a …
Chronic diseases prediction using machine learning with data preprocessing handling: a critical review
According to the World Health Organization (WHO), some chronic diseases such as
diabetes mellitus, stroke, cancer, cardiac vascular, kidney failure, and hypertension are …
diabetes mellitus, stroke, cancer, cardiac vascular, kidney failure, and hypertension are …
Predictive Analysis of Diabetes‐Risk with Class Imbalance
AI ElSeddawy, FK Karim, AM Hussein… - Computational …, 2022 - Wiley Online Library
Diabetes type 2 (T2DM) is a common chronic disease, increasingly leading to many
complications and affecting vital organs. Hyperglycemia is the main characteristic caused by …
complications and affecting vital organs. Hyperglycemia is the main characteristic caused by …
Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers
Type II diabetes mellitus (T2DM) is a rising global health burden due to its rapidly increasing
prevalence worldwide, and can result in serious complications. Therefore, it is of utmost …
prevalence worldwide, and can result in serious complications. Therefore, it is of utmost …