Coronary Artery Heart Disease Prediction: A Comparative Study of Computational Intelligence Techniques
暂无分享,去创建一个
[1] Chih-Chou Chiu,et al. Hybrid intelligent modeling schemes for heart disease classification , 2014, Appl. Soft Comput..
[2] Ashutosh Kumar,et al. Titanium dioxide nanoparticle–protein interaction explained by docking approach , 2018, International journal of nanomedicine.
[3] Qiong Chen,et al. Deep reinforcement learning for imbalanced classification , 2019, Applied Intelligence.
[4] Fevzullah Temurtas,et al. An approach based on probabilistic neural network for diagnosis of Mesothelioma's disease , 2012, Comput. Electr. Eng..
[5] G. Radhamani,et al. Prediction and analysis of Rheumatic heart disease using kNN classification with ACO , 2016, 2016 International Conference on Data Mining and Advanced Computing (SAPIENCE).
[6] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[7] Amar Mitiche,et al. A variational method to determine the most representative shape of a set of curves and its application to knee kinematic data for pathology classification , 2018, MedPRAI '18.
[8] M. M. A. Hashem,et al. Mathematical model development to detect breast cancer using multigene genetic programming , 2016, 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV).
[9] Majid Ghonji Feshki,et al. Improving the heart disease diagnosis by evolutionary algorithm of PSO and Feed Forward Neural Network , 2016, 2016 Artificial Intelligence and Robotics (IRANOPEN).
[10] D. Warkentin. Risk factors in coronary artery disease. , 1968, Journal of the Iowa Medical Society.
[11] Shraddha Dwivedi,et al. Comprehensive study of data analytics tools (RapidMiner, Weka, R tool, Knime) , 2016, 2016 Symposium on Colossal Data Analysis and Networking (CDAN).
[12] Safial Islam Ayon,et al. Diabetes Prediction: A Deep Learning Approach , 2019, International Journal of Information Engineering and Electronic Business.
[13] Kazuyuki Murase,et al. Adaptive weighted fuzzy rule-based system for the risk level assessment of heart disease , 2018, Applied Intelligence.
[14] Jiajun Zhi,et al. Support vector machine classifier for prediction of the metastasis of colorectal cancer , 2018, International journal of molecular medicine.
[15] Yong-Heng Zhao,et al. Random forest algorithm for classification of multiwavelength data , 2009 .
[16] K. Johana,et al. Benchmarking Least Squares Support Vector Machine Classifiers , 2022 .
[17] Gunasekaran Manogaran,et al. Hybrid Recommendation System for Heart Disease Diagnosis based on Multiple Kernel Learning with Adaptive Neuro-Fuzzy Inference System , 2017, Multimedia Tools and Applications.
[18] Jianping Gou,et al. A generalized mean distance-based k-nearest neighbor classifier , 2019, Expert Syst. Appl..
[19] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[20] Gholam Ali Montazer,et al. A fuzzy-evidential hybrid inference engine for coronary heart disease risk assessment , 2010, Expert Syst. Appl..
[21] Jun Li,et al. An Intelligent Parkinson's Disease Diagnostic System Based on a Chaotic Bacterial Foraging Optimization Enhanced Fuzzy KNN Approach , 2018, Comput. Math. Methods Medicine.
[22] Sunila Godara,et al. Comparative Study of Data Mining Classification Methods in Cardiovascular Disease Prediction , 2011 .
[23] T. Kemppainen,et al. Use of complementary and alternative medicine in Europe: Health-related and sociodemographic determinants , 2017, Scandinavian journal of public health.
[24] Ehsan Kazemi,et al. Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images , 2017, bioRxiv.
[25] Lekha Bhambhu,et al. DATA CLASSIFICATION USING SUPPORT VECTOR MACHINE , 2009 .
[26] José Luís Casteleiro-Roca,et al. A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine , 2018, Complex..
[27] Oliver Grimm,et al. Enabling Histopathological Annotations on Immunofluorescent Images through Virtualization of Hematoxylin and Eosin , 2018, Journal of pathology informatics.
[28] Gunasekaran Manogaran,et al. A novel Gini index decision tree data mining method with neural network classifiers for prediction of heart disease , 2018, Des. Autom. Embed. Syst..
[29] Yukako Yagi,et al. Towards machine learned quality control: A benchmark for sharpness quantification in digital pathology , 2017, Comput. Medical Imaging Graph..
[30] Md. Kamrul Hasan,et al. Prediction of breast cancer using support vector machine and K-Nearest neighbors , 2017, 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC).
[31] Ashok Ghatol,et al. Feature selection for medical diagnosis : Evaluation for cardiovascular diseases , 2013, Expert Syst. Appl..
[32] H. Hannah Inbarani,et al. A Novel Neighborhood Rough Set Based Classification Approach for Medical Diagnosis , 2015 .
[33] Kalyani Kadam,et al. Cardiovascular Disease Prediction Using Data Mining Techniques , 2019, Advances in Computational Intelligence and Robotics.
[34] X. Bui,et al. Predicting Blast-Induced Air Overpressure: A Robust Artificial Intelligence System Based on Artificial Neural Networks and Random Forest , 2018, Natural Resources Research.
[35] K. L. Bansal,et al. Comparative Study of Data Mining Tools , 2014 .
[36] G. Narsimha,et al. Energy efficient scheduling algorithm for the multicore heterogeneous embedded architectures , 2018, Des. Autom. Embed. Syst..
[37] Phayung Meesad,et al. A highly accurate firefly based algorithm for heart disease prediction , 2015, Expert Syst. Appl..
[38] Afzal Hussain Shahid,et al. Computational intelligence techniques for medical diagnosis and prognosis: Problems and current developments , 2019, Biocybernetics and Biomedical Engineering.
[39] Pedro M. Domingos,et al. On the Optimality of the Simple Bayesian Classifier under Zero-One Loss , 1997, Machine Learning.
[40] Veera Boonjing,et al. Heart Disease Classification Using Neural Network and Feature Selection , 2011, 2011 21st International Conference on Systems Engineering.
[41] Xiaoxia Liu,et al. Efficient privacy-preserving online medical primary diagnosis scheme on naive bayesian classification , 2018, Peer Peer Netw. Appl..
[42] Xuan Zhu,et al. Computational intelligence techniques and applications , 2014 .
[43] Rizwan Beg,et al. Genetic neural network based data mining in prediction of heart disease using risk factors , 2013, 2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES.
[44] Tülay Karayılan,et al. Prediction of heart disease using neural network , 2017, 2017 International Conference on Computer Science and Engineering (UBMK).
[45] Ritika Chadha,et al. Prediction of heart disease using data mining techniques , 2016, CSI Transactions on ICT.
[46] Md. Rasedul Islam,et al. Heart Disease Detection by Using Machine Learning Algorithms and a Real-Time Cardiovascular Health Monitoring System , 2018 .
[47] Richard Kijowski,et al. Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging , 2018, Magnetic resonance in medicine.
[48] Manpreet Singh,et al. Building a Cardiovascular Disease predictive model using Structural Equation Model & Fuzzy Cognitive Map , 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
[49] Usman Qamar,et al. An ensemble based decision support framework for intelligent heart disease diagnosis , 2014, International Conference on Information Society (i-Society 2014).
[50] Mehmet Emin Yuksel,et al. Classification of coronary artery disease data sets by using a deep neural network , 2017 .
[51] Ashok Kumar Dwivedi. Performance evaluation of different machine learning techniques for prediction of heart disease , 2016, Neural Computing and Applications.
[52] Norbert Schuff,et al. Locally linear embedding (LLE) for MRI based Alzheimer's disease classification , 2013, NeuroImage.
[53] Liron Pantanowitz,et al. Artificial Intelligence and Digital Pathology: Challenges and Opportunities , 2018, Journal of pathology informatics.
[54] P. Libby,et al. Braunwald's Heart Disease: A Textbook of Cardiovascular Medicine, 2-Volume Set, 9th Edition Expert Consult Premium Edition €“ Enhanced Online Features , 2011 .
[55] Sanjay Singh,et al. Effective heart disease prediction system using data mining techniques , 2018, International journal of nanomedicine.
[56] Sang Won Yoon,et al. A support vector machine-based ensemble algorithm for breast cancer diagnosis , 2017, Eur. J. Oper. Res..
[57] W. Copes,et al. Evaluating trauma care: the TRISS method. Trauma Score and the Injury Severity Score. , 1987, The Journal of trauma.
[58] Ezequiel López-Rubio,et al. Computational Intelligence Techniques in Medicine , 2015, Comput. Math. Methods Medicine.
[59] Ji Won Kim,et al. Decision tree-based technology credit scoring for start-up firms: Korean case , 2012, Expert Syst. Appl..
[60] Fevzullah Temurtas,et al. Chest diseases diagnosis using artificial neural networks , 2010, Expert Syst. Appl..
[61] Md. Kamrul Hasan,et al. Performance Evaluation of Random Forests and Artificial Neural Networks for the Classification of Liver Disorder , 2018, 2018 International Conference on Computer, Communication, Chemical, Material and Electronic Engineering (IC4ME2).
[62] Jyoti Soni,et al. Intelligent and Effective Heart Disease Prediction System using Weighted Associative Classifiers , 2011 .