International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Mammary Cancer Diagnosis using Decision Tree Classifier |
|---|---|
| ABSTRACT | Prompt identification of breast cancer significantly impacts patient outcomes in the medical field today. Women are facing different types of cancer and one among them is breast cancer which has severe impact. Breast cancer is of two types i.e. Malign or Benign type. Benign is given as a non-curable type of cancer and Malign is given as curable type of cancer. Breast cancer is symbolized by the modification of genes, persistent pain, changes in the measurement, change in shade (redness), and skin appearance of breasts. In the initial stages of breast cancer identification, algorithms such as Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and Multilayer Perceptrons (MLP) were commonly employed. By using these algorithms the accuracy of detecting the cancer is not met the extend. The Decision Tree algorithm forms the basis of our approach for detecting breast cancer and comes under the supervised learning technique. Our objective is to identify breast cancer through the application of the Decision Tree algorithm. The tree algorithm comes under the supervised learning technique. The main advantage of this decision tree algorithm is identifying whether the predicted cancer is either malign or benign type by producing an 99% accuracy. |
| TITLE | |
| AUTHOR | K. SHANDHINI, S. SARANYADEVI, R. GIRIJA, R. KALAISELVI |
| VOLUME | 176 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1311048 |
| pdf/48_Mammary Cancer Diagnosis using Decision Tree Classifier.pdf | |
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