A smart healthcare monitoring system for heart disease prediction based on ensemble deep learning and feature fusion
The accurate prediction of heart disease is essential to efficiently treating cardiac patients
before a heart attack occurs. This goal can be achieved using an optimal machine learning …
before a heart attack occurs. This goal can be achieved using an optimal machine learning …
Evolution from ancient medication to human‐centered Healthcare 4.0: A review on health care recommender systems
D Sharma, G Singh Aujla, R Bajaj - International Journal of …, 2023 - Wiley Online Library
The evolution of intelligent and data‐driven systems has pushed for the tectonic transition
from ancient medication to human‐centric Healthcare 4.0. The rise of Internet of Things …
from ancient medication to human‐centric Healthcare 4.0. The rise of Internet of Things …
Medical Internet of things using machine learning algorithms for lung cancer detection
This paper empirically evaluates the several machine learning algorithms adaptable for lung
cancer detection linked with IoT devices. In this work, a review of nearly 65 papers for …
cancer detection linked with IoT devices. In this work, a review of nearly 65 papers for …
A hybrid method for heart disease diagnosis utilizing feature selection based ensemble classifier model generation
J Abdollahi, B Nouri-Moghaddam - Iran Journal of Computer Science, 2022 - Springer
Heart disease is one of the most complicated diseases, and it affects a large number of
individuals throughout the world. In healthcare, particularly cardiology, early and accurate …
individuals throughout the world. In healthcare, particularly cardiology, early and accurate …
Machine learning techniques for heart disease datasets: A survey
Heart Failure (HF) has been proven one of the leading causes of death that is why an
accurate and timely prediction of HF risks is extremely essential. Clinical methods, for …
accurate and timely prediction of HF risks is extremely essential. Clinical methods, for …
Application of machine learning for cardiovascular disease risk prediction
Cardiovascular diseases (CVDs) are a common cause of heart failure globally. The need to
explore possible ways to tackle the disease necessitated this study. The study designed a …
explore possible ways to tackle the disease necessitated this study. The study designed a …
Empirical analysis of machine learning algorithms on imbalance electrocardiogram based arrhythmia dataset for heart disease detection
Living beings are subjected to many hazards during their course of life. Owing to high
mortality rate, heart disease (HD) is among leading hazards for living being. It is world's one …
mortality rate, heart disease (HD) is among leading hazards for living being. It is world's one …
Deep neuro‐fuzzy approach for risk and severity prediction using recommendation systems in connected health care
D Sharma, G Singh Aujla, R Bajaj - Transactions on Emerging …, 2021 - Wiley Online Library
Abstract Internet of Things (IoT) and Data science have revolutionized the entire
technological landscape across the globe. Because of it, the health care ecosystems are …
technological landscape across the globe. Because of it, the health care ecosystems are …
Method and dataset entity mining in scientific literature: a CNN+ BiLSTM model with self-attention
The traditional literature analysis mainly focuses on the literature metadata such as topics,
authors, keywords, references, and rarely pays attention to the main content of papers …
authors, keywords, references, and rarely pays attention to the main content of papers …
Systematic mapping study of AI/machine learning in healthcare and future directions
This study attempts to categorise research conducted in the area of: use of machine learning
in healthcare, using a systematic mapping study methodology. In our attempt, we reviewed …
in healthcare, using a systematic mapping study methodology. In our attempt, we reviewed …