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A comprehensive review on medical diagnosis using machine learning
The unavailability of sufficient information for proper diagnosis, incomplete or
miscommunication between patient and the clinician, or among the healthcare …
miscommunication between patient and the clinician, or among the healthcare …
Medical diagnosis using machine learning: a statistical review
Decision making in case of medical diagnosis is a complicated process. A large number of
overlap** structures and cases, and distractions, tiredness, and limitations with the human …
overlap** structures and cases, and distractions, tiredness, and limitations with the human …
Efficient data-driven machine learning models for cardiovascular diseases risk prediction
Cardiovascular diseases (CVDs) are now the leading cause of death, as the quality of life
and human habits have changed significantly. CVDs are accompanied by various …
and human habits have changed significantly. CVDs are accompanied by various …
[HTML][HTML] Heart disease risk prediction using machine learning classifiers with attribute evaluators
Cardiovascular diseases (CVDs) kill about 20.5 million people every year. Early prediction
can help people to change their lifestyles and to ensure proper medical treatment if …
can help people to change their lifestyles and to ensure proper medical treatment if …
[Retracted] Heart Disease Prediction Based on the Embedded Feature Selection Method and Deep Neural Network
D Zhang, Y Chen, Y Chen, S Ye, W Cai… - Journal of healthcare …, 2021 - Wiley Online Library
In recent decades, heart disease threatens people's health seriously because of its
prevalence and high risk of death. Therefore, predicting heart disease through some simple …
prevalence and high risk of death. Therefore, predicting heart disease through some simple …
[HTML][HTML] Integrating explainable machine learning and user-centric model for diagnosing cardiovascular disease: A novel approach
Conventional machine learning techniques in diagnosing cardiovascular disease have a
limitation owing to the lack of interpretability of models. This study utilised an explainable …
limitation owing to the lack of interpretability of models. This study utilised an explainable …
[HTML][HTML] An ensemble method based multilayer dynamic system to predict cardiovascular disease using machine learning approach
Cardiovascular disease is defined as a set of conditions related to the disorder of the heart
and blood vessels. Predicting and diagnosing cardiovascular disease is significant to …
and blood vessels. Predicting and diagnosing cardiovascular disease is significant to …
A Comprehensive Review on Heart Disease Risk Prediction using Machine Learning and Deep Learning Algorithms
Cardiovascular diseases claim approximately 17.9 million lives annually, with heart attacks
and strokes accounting for over 80% of these deaths. Key risk factors, including …
and strokes accounting for over 80% of these deaths. Key risk factors, including …
[HTML][HTML] An investigation of the constructional design components affecting the mechanical response and cellular activity of electrospun vascular grafts
Cardiovascular disease is anticipated to remain the leading cause of death globally. Due to
the current problems connected with using autologous arteries for bypass surgery …
the current problems connected with using autologous arteries for bypass surgery …
[PDF][PDF] Heart Disease Classification–Based on the Best Machine Learning Model
MM Rahma, AD Salman - Iraqi Journal of Science, 2022 - iasj.net
In recent years, predicting heart disease has become one of the most demanding tasks in
medicine. In modern times, one person dies from heart disease every minute. Within the field …
medicine. In modern times, one person dies from heart disease every minute. Within the field …