8 results for “Breast Cancer Prediction”

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Research ArticleOpen accessPhrase in the titleCross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural NetworksShirin A. Mojarad, Satnam S. Dlay, Wai L. Woo, Gajanan V. SherbetProblem statement: The presence of metastasis in the regional lymph nodes is the most important factor in predicting prognosis in breast cancer. Many biomarkers have been identified that appear to relate to the aggressive behaviour of cancer. However, the nonlinear relation of these markers to nodal status and also the existence of complex interaction between markers have prohibited an accurate … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 4 · 20 Feb 2012 · 7,699 accessesView PDF Cite

Review ArticleOpen accessEvery word in the titleVisualization of Data Mining Techniques for the Prediction of Breast Cancer with High Accuracy RatesVasudev Sharma, Raj Kumar Rajasekaran, Shreya BadhrinarayananBreast cancer is one of the leading causes of death in women worldwide. Around one in 30 women are affected by breast cancer. Mammography has helped in detecting breast cancer in the early stages which have reduced mortality. The diagnosis of breast cancer is dependent on a variety of parameters. In this paper, we aim to create the best model … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 8,948 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsPredicting the Severity of Breast Masses with Ensemble of Bayesian ClassifiersAlaa M. ElsayadProblem statement: This study evaluated two different Bayesian classifiers; tree augmented Naive Bayes and Markov blanket estimation networks in order to build an ensemble model for prediction the severity of breast masses. The objective of the proposed algorithm was to help physicians in their decisions to perform a breast biopsy on a suspicious lesion seen in a mammogram image or … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,299 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsRadial Basis Function Networks and Contrast-Limited Adaptive Histogram Equalization Filter Based Early-Stage Breast Cancer Detection TechniquesAnitha Ponraj, Aroul CanessaneBreast cancer is one of the most common types of cancer that kills women. When cells become uncontrollably large, cancer develops. As a result, detecting and classifying breast cancer in its early stages is essential so that patients can take the appropriate precautions. On the other hand, mammography images have relatively low sensitivity and effectiveness in detecting breast cancer. Furthermore, … …Journal of Computer Science, Vol. 19, Issue 6 · 25 May 2023 · 5,613 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsFine Needle Aspiration Cytology Evaluation for Classifying Breast Cancer Using Artificial Neural NetworkNor Ashidi Mat Isa, Esugasini Subramaniam, Mohd Yusoff Mashor, Nor Hayati OthmanThirteen cytology of fine needle aspiration image (i.e. cellularity, background information, cohesiveness, significant stromal component, clump thickness, nuclear membrane, bare nuclei, normal nuclei, mitosis, nucleus stain, uniformity of cell, fragility and number of cells in cluster) are evaluated their possibility to be used as input data for artificial neural network in order to classify the breast precancerous cases into four … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 7,152 accessesView PDF Cite

Research ArticleOpen accessIn the abstractIntelliHealth: A Machine Learning Driven Disease Detectionand Diet recommendation SystemAnkita Wadhwan, Priyanka Chawla, Sandeep Kaur, Usha MittalPeople all around the world are afflicted with various ailments. An accurate diagnosis can lower the risk of significant health problems developing, but an inaccurate diagnosis could have adverse implications. In this study, an ensemble-based strategy "IntelliHealth" has been presented to identify disorders of the thyroid, liver, and breast cancer using three machine learning (ML) approaches consisting of Support Vector … …Journal of Computer Science, Vol. 21, Issue 6 · 28 May 2025 · 5,226 accessesView PDF Cite

Research ArticleOpen accessIn the abstractThe Construction of Two and Three Dimensional Molecular Models for the miR-31 and Its Silencer as the Triple Negative Breast Cancer BiomarkersArli Aditya ParikesitThe Triple Negative Breast Cancer (TNBC) is considered as the most difficult Breast Cancer type to be medicated. So far, the acceptable medication and diagnostics measure are based upon the proteomics-world view, especially with utilizing the natural products and their derivatives as drug candidates. However, as the transcriptomics-studies are getting more advanced, the research on non-coding (nc)RNA is being considered … …OnLine Journal of Biological Sciences, Vol. 18, Issue 4 · 18 Oct 2018 · 7,772 accessesView PDF Cite

Research ArticleOpen accessIn the abstractFuzzy Association Rule MiningA. Lekha, C. V. Srikrishna, Viji VinodThe paper attempts to propose a fuzzy logic association algorithm to predict the risks involved in identifying diseases like breast cancer. Fuzzy logic algorithm is used to find association rules. The results of the study revealed that the prediction is better reliable than conventional methods. …Journal of Computer Science, Vol. 11, Issue 1 · 22 Sep 2014 · 7,473 accessesView PDF Cite