Cancer Prediction using Adaptive Boosting Tech Web App

doi:10.1109/icscss57650.2023.10169748

Paper

Cancer Prediction using Adaptive Boosting Tech Web App

Published Jun 14, 2023 · DOI · T. Keerthika, S. Kanimozhi, V. Oviya Svapna

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)

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Abstract

Cancer is a complaint that is characterized by the development of abnormal cells that multiply themselves and spread to the other parts of the body. Breast cancer is one that spreads in the cells of the breast. It can occur in one or both breasts. Generally, it occurs in women but in a rare case, it occurs in men. The cause of breast cancer can be due to regular activities like food intake, smoking, tobacco, intake of alcoholic content, etc. It can also be caused due to genetics. This study presents a web app using the Adaptive Boosting technique for detecting breast cancer which is trained and estimated on numerical data such as mean_radius, area_error, smoothness-error, etc. After analysis the Adaptive Boosting (AdaBoost) model has achieved 97% accuracy compared to other algorithms. Further these algorithms can be modified with their mathematical models to increase the prediction of breast cancer.

Study Snapshot

The AdaBoost web app accurately detects breast cancer with 97% accuracy compared to other algorithms, making it a promising tool for breast cancer detection.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

Cancer Prediction using Adaptive Boosting Tech Web App

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