Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction

By S. Jyoti, Ansari Ujma, Sharma Dipesh, S.K. Sunita. 2011

801 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Information Management, Information Systems

View Paper: https://www.semanticscholar.org/paper/fbd65a18f6653b56138cd5196d20e2f39de189e3

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Citations in the corpus

Performance Evaluation of Machine Learning Algorithms in Post-operative Life Expectancy in the Lung Cancer Patients (2015, background): “Decision Tree is a popular classifier in machine learning environment that is simple and easy to implement, and requires no domain knowledge or parameter setting and can handle high dimensional data, more appropriate for exploratory knowledge discovery and analysis [32-33].”
Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance (2021, background): “Every year, almost 12 million people die due to heart diseases [3].”
Heart disease prediction using supervised machine learning algorithms: Performance analysis and comparison (2021, methodology): “In 2011, Jyoti Soni et al. applied DT with a genetic algorithm to improve the classification performance, and this was compared with other two algorithms such as NB and classification via cluster methods [9].”
Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm (2017, background): “In fact, a large number of investigations have been conducted in this field [12-34], with the UCI datasets [35] being the most frequently utilized sets.”
A survey on Data Mining approaches for Healthcare (2013, methodology): “Data Mining are also used for both analysis and prediction of various diseases [14-23].”
Effective Heart Disease Prediction Using Machine Learning Techniques (2023, background): “In the medical ﬁeld, a vast amount of data is generated daily using data mining techniques, and we can ﬁnd hidden patterns that can be used for clinical diagnosis [10].”
Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural networks, and functional trees methods (2017, background): “NB is a statistical classifier based on hypothesis that there is not any dependency between attributes to maximize the posterior probability in determination of the class for classification (Soni et al. 2011).”