Heart disease prediction using machine learning techniques: a quantitative review
Heart diseases or the cardiovascular diseases are the main reasons for a large number of
deaths in the world today. Heart disease affects the functioning of blood vessels and can …
deaths in the world today. Heart disease affects the functioning of blood vessels and can …
Efficient prediction of cardiovascular disease using machine learning algorithms with relief and LASSO feature selection techniques
Cardiovascular diseases (CVD) are among the most common serious illnesses affecting
human health. CVDs may be prevented or mitigated by early diagnosis, and this may reduce …
human health. CVDs may be prevented or mitigated by early diagnosis, and this may reduce …
Disease detection and prediction using the liver function test data: A review of machine learning algorithms
In the last decade, there has been an admirable improvement in the classification accuracy
of various machine learning techniques used for disease diagnosis. This even aids in …
of various machine learning techniques used for disease diagnosis. This even aids in …
Incorporating cnn features for optimizing performance of ensemble classifier for cardiovascular disease prediction
Cardiovascular diseases (CVDs) have been regarded as the leading cause of death with
32% of the total deaths around the world. Owing to the large number of symptoms related to …
32% of the total deaths around the world. Owing to the large number of symptoms related to …
A machine learning approach to detect the brain stroke disease
The brain, which comprises the cerebrum, cere-bellum, and brainstem and is covered by the
skull, is a very complex and intriguing organ in the human body. Stroke is the world's second …
skull, is a very complex and intriguing organ in the human body. Stroke is the world's second …
[PDF][PDF] Numerical and experimental investigation of meteorological data using adaptive linear M5 model tree for the prediction of rainfall
Real-time predictions are always important for accurate and systematic thinking in planning
future processes. The failure in the availability of current machine learning approaches is a …
future processes. The failure in the availability of current machine learning approaches is a …
A fully connected quantum convolutional neural network for classifying ischemic cardiopathy
U Ullah, AGO Jurado, ID Gonzalez… - IEEE …, 2022 - ieeexplore.ieee.org
The prevalence of heart diseases is rising quickly throughout the world, which has an impact
on both the world economy and public health. According to the recent statistical survey …
on both the world economy and public health. According to the recent statistical survey …
A survey of medical image analysis using deep learning approaches
With the expanding development of Deep Learning techniques Medical Image Analysis
have become an active field of research. Medical Image Analysis typically refers to the …
have become an active field of research. Medical Image Analysis typically refers to the …
A pragmatic comparison of supervised machine learning classifiers for disease diagnosis
This study focuses on comparing the different supervised machine learning classifiers such
as Logistic Regression, Naïve Bayes, Support Vector Machine, K-Nearest Neighbour …
as Logistic Regression, Naïve Bayes, Support Vector Machine, K-Nearest Neighbour …
Knowledge discovery in geographical sciences—A systematic survey of various machine learning algorithms for rainfall prediction
One of the biggest challenges faced by humanity over time is weather prediction. Rainfall
prediction plays a critical role in agricultural sciences, besides it is pivotal in the prediction of …
prediction plays a critical role in agricultural sciences, besides it is pivotal in the prediction of …