Brest Cancer Predictor Using Machine Learning

The problem of the Breast Cancer around the world among women becoming worsens each passing day. Curing of Breast Cancer disease is never easy for women. It is also become hard when women are in there 30’s. After several research or experiments by our doctors and scientists, there is no 100% curable treatment for the cancer. In India, in every 4 minutes one women is diagnosed with breast cancer and in every 13 minutes one women died due to breast cancer. Researchers are predicting that by 2030 in India the most deaths among women will be due to breast cancer. We can also say that due to lack of accurate prediction models results in the difficulty for doctors to prepare for a treatment plan. So, we must develop a model which gives good accuracy with minimum errors in less time. Three types of algorithms SVM, AdaBoost, XgBoost which predict the breast cancer will be discussed. All these algorithms will be executed and conducted on JUPYTER Notebook platform. This work is done to predict the outcomes of different types of techniques and which technique has good accuracy.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-24
DOI
https://doi.org/10.5281/zenodo.15086999
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Brest Cancer Predictor Using Machine Learning

Zenodo (CERN European Organization for Nuclear Research)
Gene expression and cancer classification
article

Brest Cancer Predictor Using Machine Learning

article en

Abstract

The problem of the Breast Cancer around the world among women becoming worsens each passing day. Curing of Breast Cancer disease is never easy for women. It is also become hard when women are in there 30’s. After several research or experiments by our doctors and scientists, there is no 100% curable treatment for the cancer. In India, in every 4 minutes one women is diagnosed with breast cancer and in every 13 minutes one women died due to breast cancer. Researchers are predicting that by 2030 in India the most deaths among women will be due to breast cancer. We can also say that due to lack of accurate prediction models results in the difficulty for doctors to prepare for a treatment plan. So, we must develop a model which gives good accuracy with minimum errors in less time. Three types of algorithms SVM, AdaBoost, XgBoost which predict the breast cancer will be discussed. All these algorithms will be executed and conducted on JUPYTER Notebook platform. This work is done to predict the outcomes of different types of techniques and which technique has good accuracy.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 63%
Gene expression and cancer classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Brest Cancer Predictor Using Machine Learning · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS