Enhancing the early detection of chronic kidney disease: a robust machine learning model
Clinical decision-making in chronic disorder prognosis is often hampered by high variance,
leading to uncertainty and negative outcomes, especially in cases such as chronic kidney …
leading to uncertainty and negative outcomes, especially in cases such as chronic kidney …
Heart disease detection using ml
Hearth disease is one of the leading causes of death globally and a common disease in the
middle and old ages. Among all heart diseases, heart attack and strokes are the most …
middle and old ages. Among all heart diseases, heart attack and strokes are the most …
Machine learning approaches for predicting and diagnosing chronic kidney disease: current trends, challenges, solutions, and future directions
P Gogoi, JA Valan - International Urology and Nephrology, 2024 - Springer
Abstract Chronic Kidney Disease (CKD) represents a significant global health challenge,
contributing to increased morbidity and mortality rates. This review paper explores the …
contributing to increased morbidity and mortality rates. This review paper explores the …
Machine Learning-Based Relative Performance Analysis for Breast Cancer Prediction
The current high population growth in medical research has made early disease
identification an urgent issue. The danger of dying from breast cancer is increasing …
identification an urgent issue. The danger of dying from breast cancer is increasing …
SARS CovidAID: Automatic detection of SARS CoV-19 cases from CT scan images with pretrained transfer learning model (VGG19, RESNet50 and DenseNet169) …
The COVID-19 outbreak has presented significant challenges to medical professionals
worldwide and underscored the need for accurate and effective detection methods due to its …
worldwide and underscored the need for accurate and effective detection methods due to its …
A comparative study of machine learning approaches for heart stroke prediction
The majority of strokes are triggered by the heart and brain blocking expected pathways.
Today, it is the most common cause of death in the worldwide. By looking at the people …
Today, it is the most common cause of death in the worldwide. By looking at the people …
Ensemble machine learning framework for predicting maternal health risk during pregnancy
Maternal health risks can cause a range of complications for women during pregnancy. High
blood pressure, abnormal glucose levels, depression, anxiety, and other maternal health …
blood pressure, abnormal glucose levels, depression, anxiety, and other maternal health …
[PDF][PDF] Comparison of the Error Rates of MNIST Datasets Using Different Type of Machine Learning Model
The MNIST dataset is a popular benchmark dataset in the field of machine learning and
computer vision. The dataset has a training set of 60,000 examples, and a test set of 10,000 …
computer vision. The dataset has a training set of 60,000 examples, and a test set of 10,000 …
A harmful disorder: Predictive and comparative analysis for fetal Anemia disease by using different machine learning approaches
Anemia is a major issue for public health with significant implications for national
development, it remains a largely neglected health problem in many develo** countries …
development, it remains a largely neglected health problem in many develo** countries …
KidneyMultiNet: A Web-Based Automatic System for Kidney Disease Detection Using Hybrid Machine Learning Model From CT Scan Images
Chronic renal disease is the term used to describe kidney function that gradually declines.
The kidneys' final byproduct of eliminating waste and surplus fluid from the bloodstream is …
The kidneys' final byproduct of eliminating waste and surplus fluid from the bloodstream is …