Z-Alizadeh-Sani数据集

Data Set Information: 每个患者可能分为两类：冠心病或正常。如果患者的直径变窄大于或等于50%，则将其归类为CAD，否则视为正常。 Attribute Information: Z-Alizadeh Sani数据集包含303名患者的记录，每个患者有54个特征。这些特征分为四组：人口统计学、症状和检查、心电图、实验室和回声特征。 Relevant Papers: R. Alizadehsani, J. Habibi, M. J. Hosseini, H. Mashayekhi, R. Boghrati, A. Ghandeharioun, et al., 'A data mining approach for diagnosis of coronary artery disease,' Computer Methods and Programs in Biomedicine, vol. 111, pp. 52-61, 2013/07/01/ 2013. R. Alizadehsani, J. Habibi, B. Bahadorian, H. Mashayekhi, A. Ghandeharioun, R. Boghrati, et al., 'Diagnosis of Coronary Arteries Stenosis Using Data Mining,' Journal of Medical Signals and Sensors, vol. 2, pp. 153-159, Jul-Sep R. Alizadehsani, M. J. Hosseini, Z. A. Sani, A. Ghandeharioun, and R. Boghrati, 'Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms,' in 2012 IEEE 12th International Conference on Data Mining Workshops, 2012, pp. 9-16. Z. Arabasadi, R. Alizadehsani, M. Roshanzamir, H. Moosaei, and A. A. Yarifard, 'Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm,' Computer Methods and Programs in Biomedicine, vol. 141, pp. 19-26, 2017/04/01/ 2017. R. Alizadehsani, J. Habibi, Z. Alizadeh Sani, H. Mashayekhi, R. Boghrati, A. Ghandeharioun, et al., 'Diagnosing Coronary Artery Disease via Data Mining Algorithms by Considering Laboratory and Echocardiography Features,' Research in Cardiovascular Medicine, vol. 2, pp. 133-139, 07/31 R. Alizadehsani, J. Habibi, M. J. Hosseini, R. Boghrati, A. Ghandeharioun, B. Bahadorian, et al., 'Diagnosis of coronary artery disease using data mining techniques based on symptoms and ecg features,' European Journal of Scientific Research, vol. 82, pp. 542-553, 2012. R. Alizadehsani, M. H. Zangooei, M. J. Hosseini, J. Habibi, A. Khosravi, M. Roshanzamir, et al., 'Coronary artery disease detection using computational intelligence methods,' Knowledge-based Systems, vol. 109, pp. 187-197, 2016/10/01/ 2016. R. Alizadehsani, J. Habibi, Z. A. Sani, H. Mashayekhi, R. Boghrati, A. Ghandeharioun, et al., 'Diagnosis of Coronary Artery Disease Using Data mining based on Lab Data and Echo Features,' Journal of Medical and Bioengineering, vol. 1, 2012. A. Roohallah, H. Mohammad Javad, B. Reihane, G. Asma, K. Fahime, and S. Zahra Alizadeh, 'Exerting Cost-Sensitive and Feature Creation Algorithms for Coronary Artery Disease Diagnosis,' International Journal of Knowledge Discovery in Bioinformatics (IJKDB), vol. 3, pp. 59-79, 2012. R. Alizadehsani, M. J. Hosseini, Z. Alizadehsani, M. H. Mohammadi, O. Barati, and F. Khozeimeh, 'System for determining the need for Angiography in patients with symptoms of Coronary Artery disease,' ed: Google Patents, 2014. F. Babi??, J. Olej??r, Z. Vantov??, and J. Parali??, 'Predictive and Descriptive Analysis for Heart Disease Diagnosis,' presented at the Federated Conference on Computer Science and Information Systems, 2017. LOHITA, Kodali et al. Performance Analysis of Various Data Mining Techniques in the Prediction of Heart Disease. Indian Journal of Science and Technology, [S.l.], dec. 2015. ISSN 0974 -5645. Available at: <[Web link]>. Date accessed: 17 Nov. 2017. [Web link]. J. Bekta??, T. Ibrik?§i, and I. ?–zcan, 'Classification of Real Imbalanced Cardiovascular Data Using Feature Selection and Sampling Methods: A Case Study with Neural Networks and Logistic Regression,' International Journal on Artificial Intelligence Tools, 2017. C. Yadav, S. Lade, and M. K. Suman, 'Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining,' International Journal of Computer Applications, vol. 87, 2014.

数据集信息：所有患者将被分为两类：冠心病（Coronary Artery Disease, CAD）或正常。若患者的血管直径狭窄程度≥50%，则将其归类为冠心病（CAD），否则视为正常。
属性信息：Z-Alizadeh Sani数据集（Z-Alizadeh Sani Dataset）包含303名患者的诊疗记录，每位患者对应54项特征。这些特征分为四大类：人口统计学特征、症状与检查特征、心电图（Electrocardiogram, ECG）特征、实验室检查与超声心动图特征。
相关研究文献：
1. R. Alizadehsani、J. Habibi、M. J. Hosseini、H. Mashayekhi、R. Boghrati、A. Ghandeharioun等，"A data mining approach for diagnosis of coronary artery disease"，《Computer Methods and Programs in Biomedicine》，第111卷，第52-61页，2013年7月1日，2013年。
2. R. Alizadehsani、J. Habibi、B. Bahadorian、H. Mashayekhi、A. Ghandeharioun、R. Boghrati等，"Diagnosis of Coronary Arteries Stenosis Using Data Mining"，《Journal of Medical Signals and Sensors》，第2卷，第153-159页，7-9月。
3. R. Alizadehsani、M. J. Hosseini、Z. A. Sani、A. Ghandeharioun、R. Boghrati，"Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms"，收录于2012 IEEE第12届国际数据挖掘研讨会（2012 IEEE 12th International Conference on Data Mining Workshops），2012年，第9-16页。
4. Z. Arabasadi、R. Alizadehsani、M. Roshanzamir、H. Moosaei、A. A. Yarifard，"Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm"，《Computer Methods and Programs in Biomedicine》，第141卷，第19-26页，2017年4月1日，2017年。
5. R. Alizadehsani、J. Habibi、Z. Alizadeh Sani、H. Mashayekhi、R. Boghrati、A. Ghandeharioun等，"Diagnosing Coronary Artery Disease via Data Mining Algorithms by Considering Laboratory and Echocardiography Features"，《Research in Cardiovascular Medicine》，第2卷，第133-139页，7月31日。
6. R. Alizadehsani、J. Habibi、M. J. Hosseini、R. Boghrati、A. Ghandeharioun、B. Bahadorian等，"Diagnosis of coronary artery disease using data mining techniques based on symptoms and ecg features"，《European Journal of Scientific Research》，第82卷，第542-553页，2012年。
7. R. Alizadehsani、M. H. Zangooei、M. J. Hosseini、J. Habibi、A. Khosravi、M. Roshanzamir等，"Coronary artery disease detection using computational intelligence methods"，《Knowledge-based Systems》，第109卷，第187-197页，2016年10月1日，2016年。
8. R. Alizadehsani、J. Habibi、Z. A. Sani、H. Mashayekhi、R. Boghrati、A. Ghandeharioun等，"Diagnosis of Coronary Artery Disease Using Data mining based on Lab Data and Echo Features"，《Journal of Medical and Bioengineering》，第1卷，2012年。
9. A. Roohallah、H. Mohammad Javad、B. Reihane、G. Asma、K. Fahime、S. Zahra Alizadeh，"Exerting Cost-Sensitive and Feature Creation Algorithms for Coronary Artery Disease Diagnosis"，《International Journal of Knowledge Discovery in Bioinformatics (IJKDB)》，第3卷，第59-79页，2012年。
10. R. Alizadehsani、M. J. Hosseini、Z. Alizadehsani、M. H. Mohammadi、O. Barati、F. Khozeimeh，"System for determining the need for Angiography in patients with symptoms of Coronary Artery disease"，Google Patents，2014年。
11. F. Babi??、J. Olej??、Z. Vantov??、J. Parali??，"Predictive and Descriptive Analysis for Heart Disease Diagnosis"，收录于2017年联邦计算机科学与信息系统会议（Federated Conference on Computer Science and Information Systems），2017年。
12. LOHITA、Kodali等，"Performance Analysis of Various Data Mining Techniques in the Prediction of Heart Disease"，《Indian Journal of Science and Technology》，[出版地不详]，2015年12月。ISSN 0974-5645。可获取链接：<[Web link]>。访问日期：2017年11月17日。[Web link]。
13. J. Bekta??、T. Ibrik?§i、I. ?–zcan，"Classification of Real Imbalanced Cardiovascular Data Using Feature Selection and Sampling Methods: A Case Study with Neural Networks and Logistic Regression"，《International Journal on Artificial Intelligence Tools》，2017年。
14. C. Yadav、S. Lade、M. K. Suman，"Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining"，《International Journal of Computer Applications》，第87卷，2014年。

搜集汇总

背景与挑战

背景概述

Z-Alizadeh-Sani数据集是一个用于冠心病诊断的医学数据集，包含303名患者的54个特征，覆盖人口统计学、症状、心电图和实验室数据等多方面信息。数据集通过冠状动脉直径变窄程度（≥50%）将患者分类为冠心病或正常，适用于数据挖掘和机器学习在医疗诊断中的应用。