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Diagnosing Breast Cancer Based on Support Vector Machines

H. X. Liu, R. S. Zhang, F. Luan, X. J. Yao, M. C. Liu, Z. D. Hu, B. T. Fan
2003 Journal of chemical information and computer sciences  
The Support Vector Machine (SVM) classification algorithm, recently developed from the machine learning community, was used to diagnose breast cancer.  ...  SVM outperformed k-means cluster and two artificial neural networks on the whole. It can be concluded that nine samples could be mislabeled from the comparison of several machine learning techniques.  ...  ACKNOWLEDGMENT The authors thank the Association Franco-Chinoise pour la Recherche Scientifique & Technique (AFCRST) for supporting this study (Program PRA SI 00-05).  ... 
doi:10.1021/ci0256438 pmid:12767148 fatcat:tylhqfl6njbb3pj6qvpppbk4re

Linear discriminant analysis and support vector machines for classifying breast cancer

Zuherman Rustam, Yasirly Amalia, Sri Hartini, Glori Stephani Saragih
2021 IAES International Journal of Artificial Intelligence (IJ-AI)  
A specialist doctor will diagnose the patient and give treatment based on the diagnosis which is benign or malignant. Machine learning offer times efficiency to determine a cancer cell.  ...  The machine will learn the pattern based on the information from the dataset.  ...  ACKNOWLEDGEMENT This research supported financially by University of Indonesia, with a DRPM PUTI Q2 2020 research grant scheme.  ... 
doi:10.11591/ijai.v10.i1.pp253-256 fatcat:o2wdsxlu4vhf3bi7desmczvltu

Support Vector Machine Classifier for Prediction of Breast Malignancy using Wisconsin Breast Cancer Dataset

Reddy Anuradha
2021 Asian journal of convergence in technology  
Support Vector Machine is a supervised learning technique (SVM). The SVM classifier's classification performance is evaluated.  ...  This is one of the primary causes of female death in the world. Breast cancer kills one out of every eleven women around the world.  ...  The breast cancer model is described as a classification job in this article, and the Support Vector Machine (SVM) approach is used to classify breast cancer as benign or malignant.  ... 
doi:10.33130/ajct.2021v07i03.010 fatcat:qn3bh2j2ivfbliypxdpsmo4mv4

Breast Cancer Diagnosis Using Machine Learning Algorithms - A Survey

Gayathri B.M, Sumathi C.P, Santhanam T
2013 International Journal of Distributed and Parallel systems  
This paper summarizes the survey on breast cancer diagnosis using various machine learning algorithms and methods, which are used to improve the accuracy of predicting cancer.  ...  Waiting for diagnosing a breast cancer for a long time may increase the possibility of the cancer spreading.  ...  Hence Relevance vector machine can also be applied to attain best result for diagnosing breast cancer.  ... 
doi:10.5121/ijdps.2013.4309 fatcat:kfvydgzyqnhlnfj2p7s53ba6zu

Breast Cancer Prediction using KNN, SVM, Logistic Regression and Decision Tree

Vattsal Singhal, Yuvraj Chaudhary, Sanidhya Verma, Umang Agarwal, Mr. Paramanand Sharma
2022 International Journal for Research in Applied Science and Engineering Technology  
In this study, we applied five machine learning algorithms: Support Vector Machine (SVM), RandomForest, Logistic Regression, Decision tree (C4.5) and K-Nearest Neighbours (KNN) on the Breast Cancer WisconsinDiagnostic  ...  It is observed that Support vector Machine outperformed all other classifiers and achieved the highest accuracy (97.2%).  ...  probabilistic vector support machine.  ... 
doi:10.22214/ijraset.2022.42688 fatcat:tvalohhavvhkjdcyfkeojt2oia

Machine Learning Algorithms For Breast Cancer Prediction And Diagnosis

Mohammed Amine Naji, Sanaa El Filali, Kawtar Aarika, EL Habib Benlahmar, Rachida Ait Abdelouhahid, Olivier Debauche
2021 Procedia Computer Science  
In this study, we applied five machine learning algorithms: Support Vector Machine (SVM), Random Forest, Logistic Regression, Decision tree (C4.5) and K-Nearest Neighbours (KNN) on the Breast Cancer Wisconsin  ...  It is observed that Support vector Machine outperformed all other classifiers and achieved the highest accuracy (97.2%).All the work is done in the Anaconda environment based on python programming language  ...  probabilistic vector support machine.  ... 
doi:10.1016/j.procs.2021.07.062 fatcat:iizanr6objhm7ebdf2t6rogesq

Using Five Machine Learning for Breast Cancer Biopsy Predictions Based on Mammographic Diagnosis

David Oyewola, Danladi Hakimi, Kayode Adeboye, Musa Danjuma Shehu
2017 International Journal of Engineering Technologies IJET  
Therefore, Support Vector Machine (SVM) learning classification with mammography can provide highly accurate and consistent diagnoses in distinguishing malignant and benign cases for breast cancer predictions  ...  Furthermore, an estimated area of the receiver operating characteristic (ROC) curve analysis for Support vector machine (SVM) was 99.9% for breast cancer outcome predictions, outperformed the diagnostic  ...  This subspace randomization scheme is blended with bagging (Breiman, 1996 Support Vector Machine (SVM) Support vector machine (SVM) is a powerful machine learning technique for classification.  ... 
doi:10.19072/ijet.280563 fatcat:dmlzoogvtff73mwuv2o5ce32me

Machine Learning Techniques and Extreme Learning Machine for Early Breast Cancer Prediction

Breast Cancer is one of the most deadly disease and most of the women are infected by this vital disease in many parts of the world.  ...  The dataset available publically for Breast Cancer has been used.  ...  In [10] , the dataset was taken from Iranian centre of breast cancer and compared decision tree, support vector machine and artificial neural network.  ... 
doi:10.35940/ijitee.d1411.029420 fatcat:jzkuyc4er5aq3hxoyxpklp52nm


Neha Kumari, Bansal Institute of Science and Technology, Bhopal, India
2019 International Journal of Advanced Research in Computer Science  
Due to this reason cancer detection in the early stage is one of the favorite areas of the researcher. In the past few decades, several machine learning approach has been used by various researchers.  ...  Now a day's cancer is one of the main decreases in all over the world. Several peoples have died in a day.  ...  The performances were compared against support vector machines, learning vector quantization, decision tree induction, and other methods based on two-breast cancer data set, sufficient and insufficient  ... 
doi:10.26483/ijarcs.v10i3.6438 fatcat:v33tojozhvhl7koylrrqni6zq4

Breast Cancer Detection Using Machine Learning

Karthikeyan B
2020 International Journal of Advanced Trends in Computer Science and Engineering  
The implementation of this project is done by using Machine Learning techniques on data from the UCI Machine Learning Repository Data Set.  ...  Among different cancers, the most invasive and menacing cancer in women is breast cancer. Women in 140 of 184 countries across the world, continually gets affected by this.  ...  So, based on accuracy Support Vector Machines is selected [11] . Sri Hari Nallamala et. Al.  ... 
doi:10.30534/ijatcse/2020/12922020 fatcat:zm7eyjdzlbbjjlos4zyrmsvs6m

Comparative Evaluation of Machine Learning Algorithms in Breast Cancer

2022 Qalaai Zanist Scientific Journal  
Breast cancer is one of the world's leading causes of mortality in women and is due to uncontrollable breast cell growth. Early detection and proper care are the only means of  ...  Machine learning approaches are used to diagnose cancer and identify cancer like the support vector network, the Bayesian confidence network, and the artificial neural network (P. Suryachandra and P.  ...  Sumathi, 2015) 4 Support A significance vector machine learning technique is Vector 97% used to classify cancer. (A.  ... 
doi:10.25212/lfu.qzj.7.1.34 fatcat:gd6mjuu7urdmdki6x4nb55lmpa

Application of Machine Learning and Word Embeddings in the Classification of Cancer Diagnosis Using Patient Anamnesis

Andres Ramos, Hector Allende-Cid, Carla Taramasco, Carlos Becerra, Rosa L. Figueroa
2020 IEEE Access  
categories: breast cancer, cysts and nodules, other cancer, breast cancer surgeries and other diagnoses; and the other dataset was obtained from the MIMIC III dataset.  ...  'breast cancer' versus 'other cancer'.  ...  The algorithms and their parameters are presented as follows: • Support Vector Machines: A support vector machine is a supervised machine learning algorithm that permits classifying the data by a separating  ... 
doi:10.1109/access.2020.3000075 fatcat:lconzczz6vf27hvsxhr4j36xae

Predicting the Possibility of Cancer with Supervised learning Algorithms

2020 International Journal of Emerging Trends in Engineering Research  
This leads to extensive research in the diagnosis and classification of patients based on its malignancy. Lot of machine learning algorithms was used to diagnose this disease.  ...  According to the statistics, the disease with which most of the women die is breast cancer. Lot of new cases and deaths because of this cancer places this disease as a major public health issue.  ...  The classification is done based on different algorithms like Nearest Neighbor, Support Vector Machines, Naive Bayes and Decision Tree Algorithm.  ... 
doi:10.30534/ijeter/2020/47892020 fatcat:iwrmdib6qfgfrh3faxxoogxgfu

Diagnosing Breast Cancer Accurately Based on Weighting of Heterogeneous Classification Sub-Models

Majdy Mohamed Eltayeb Eltahir, Tarig Mohammed Ahmed
2022 Computer systems science and engineering  
The model can work as a strong decision support system to help doctors to make the right decision in diagnosing breast cancer patients.  ...  In developed and developing countries, breast cancer is one of the leading forms of cancer affecting women alike.  ...  A performance distinction is made in this analysis on the Wisconsin Breast Cancer datasets from the data sets of the UCI Machine Learning Repository between different support vector machine (SVM) machine  ... 
doi:10.32604/csse.2022.022942 fatcat:zl3euf6orjbt7emun5pbteru5m


Radhanath Patra, ShankhaMitra Sunani.
2016 International Journal of Advanced Research  
on (RVM)relevance vector machine for diagnosis of breast cancer database [19] .  ...  Álvarez Menéndez introduced a SOM based clustering algorithm and examined the polynomial kernel of Support Vector Machines (SVM) in actual clinical diagnosis of breast cancer.  ... 
doi:10.21474/ijar01/2123 fatcat:4vyz65gw3jc4bkgyaqfw4llz4u
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