An ensemble approach to predict early-stage diabetes risk using machine learning: An empirical study
Diabetes is a long-lasting disease triggered by expanded sugar levels in human blood and
can affect various organs if left untreated. It contributes to heart disease, kidney issues …
can affect various organs if left untreated. It contributes to heart disease, kidney issues …
Glycation-associated diabetic nephropathy and the role of long noncoding RNAs
The glycation of various biomolecules is the root cause of many pathological conditions
associated with diabetic nephropathy and end-stage kidney disease. Glycation imbalances …
associated with diabetic nephropathy and end-stage kidney disease. Glycation imbalances …
Optimizing diabetes classification with a machine learning-based framework
X Feng, Y Cai, R Xin - BMC bioinformatics, 2023 - Springer
Background Diabetes is a metabolic disorder usually caused by insufficient secretion of
insulin from the pancreas or insensitivity of cells to insulin, resulting in long-term elevated …
insulin from the pancreas or insensitivity of cells to insulin, resulting in long-term elevated …
Improved diabetes prediction with reduced feature sets: Evaluating feature selection techniques in machine learning
Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels,
which can lead to various health complications. Manual assessments for diabetes prediction …
which can lead to various health complications. Manual assessments for diabetes prediction …
Tabular data generation to improve classification of liver disease diagnosis
Liver diseases are among the most common diseases worldwide. Because of the high
incidence and high mortality rate, these diseases diagnoses are vital. Several elements …
incidence and high mortality rate, these diseases diagnoses are vital. Several elements …
Chronic Diseases Prediction Using Machine Learning With Data Preprocessing Handling: A Critical Review
NG Ramadhan, W Maharani, AA Gozali - IEEE Access, 2024 - ieeexplore.ieee.org
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 …
Integrative analysis of Mendelian randomization and gene expression profiles reveals a null causal relationship between adiponectin and diabetic retinopathy
A Zhang, H Wu, C Wang, S Tian - Adipocyte, 2023 - Taylor & Francis
Observational studies have been conducted to investigate the correlation between
adiponectin and diabetic retinopathy (DR), but no consistent relationship has been …
adiponectin and diabetic retinopathy (DR), but no consistent relationship has been …
Exploring Hyper-Parameters and Feature Selection for Predicting Non-Communicable Chronic Disease Using Stacking Classifier
Non-communicable disease, especially chronic disease, is the most common factor of
complication of deteriorating physical health and the state of one's mind. It is also a …
complication of deteriorating physical health and the state of one's mind. It is also a …
Critical Factor Analysis for prediction of Diabetes Mellitus using an Inclusive Feature Selection Strategy
E Sreehari, LDD Babu - Applied Artificial Intelligence, 2024 - Taylor & Francis
Diabetes mellitus is a metabolic disorder that significantly implicates serious consequences
in various parts of the human body, such as the Eye, Heart, kidney, Nerves, Foot, etc. The …
in various parts of the human body, such as the Eye, Heart, kidney, Nerves, Foot, etc. The …
The Exploring feature selection techniques on Classification Algorithms for Predicting Type 2 Diabetes at Early Stage
MD Anasanti, K Hilyati, A Novtariany - Jurnal RESTI (Rekayasa …, 2022 - jurnal.iaii.or.id
Predicting early Type 2 diabetes (T2D) is critical for improved care and better T2D outcomes.
An accurate and efficient T2D prediction relies on unbiased relevant features. In this study …
An accurate and efficient T2D prediction relies on unbiased relevant features. In this study …