International application of a new probability algorithm for the diagnosis of coronary artery disease.

By R. Detrano, A. Jánosi, W. Steinbrunn, M. Pfisterer, J. Schmid, S. Sandhu, K. Guppy, Stella Lee, V. Froelicher. 1989

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Citations in the corpus

Semi-supervised learning, causality, and the conditional cluster assumption (2019, methodology): “For our conditional self-learning algorithm we use linear ridge regression [27] Medical data As real world data, due to the fact that both plausibly contain cause and effect features, we chose the two medical datasets Pima Indians Diabetes [28] and Heart Disease [29].”
Supersparse linear integer models for optimized medical scoring systems (2015, background): “(1995) 683 9 detect breast cancer using a biopsy bankruptcy Kim and Han (2003) 250 6 predict if a firm will go bankrupt haberman Haberman (1976) 306 3 predict 5-year survival after breast cancer surgery heart Detrano et al. (1989) 303 32 identify patients a high risk of heart disease mammo Elter et ”
Heart Disease Identification Method Using Machine Learning Classification in E-Healthcare (2020, methodology): “Cleveland heart disease dataset 2016 [11] and [12].”
Federated Learning for Healthcare Informatics (2019, background): “Disease prediction [33] NN 5, 10 Pima Indians Diabetes Dataset [95], Cleveland Heart Disease Database [23]”
Analysis of the consistency of a mixed integer programming-based multi-category constrained discriminant model (2010, background): “Five of the data sets (wine, iris, new-thyroid, sepal, and FNlnVN ) are 3-group data sets, and four are 5-group data sets (va, switzerland, hungarian, cleveland [7]).”
TabLLM: Few-shot Classification of Tabular Data with Large Language Models (2022, unknown): “• Heart Failure Prediction retrieved from Kaggle1, containing data collected at four different hospital systems (Detrano et al., 1989).”
Heart Disease Prediction Using Machine Learning Algorithms (2024, background): “Yun et al.[6] introduced various approaches for feature selection tailored to different scenarios, including high-dimensional small sample size data, large-scale data, and secure feature selection.”
Multivariate decision trees using linear discriminants and tabu search (2003, background): “Cleveland. This heart disease dataset was collected at the Cleveland Clinic Foundation [ 11 ].”
A Hybrid Intelligent System Framework for the Prediction of Heart Disease Using Machine Learning Algorithms (2018, methodology): “0e Cleveland heart disease dataset has been implemented in several studies [13] and is used in our study.”