Devising a solution to the problems of Cancer awareness in Telangana

Fuente: arXiv
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Autores principales: Avhad, Priyanka, Kshirsagar, Vedanti, Ranjan, Urvi, Nakhua, Mahek
Formato: Preprint
Publicado: 2025
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author Avhad, Priyanka
Kshirsagar, Vedanti
Ranjan, Urvi
Nakhua, Mahek
author_facet Avhad, Priyanka
Kshirsagar, Vedanti
Ranjan, Urvi
Nakhua, Mahek
contents According to the data, the percent of women who underwent screening for cervical cancer, breast and oral cancer in Telangana in the year 2020 was 3.3 percent, 0.3 percent and 2.3 percent respectively. Although early detection is the only way to reduce morbidity and mortality, people have very low awareness about cervical and breast cancer signs and symptoms and screening practices. We developed an ML classification model to predict if a person is susceptible to breast or cervical cancer based on demographic factors. We devised a system to provide suggestions for the nearest hospital or Cancer treatment centres based on the users location or address. In addition to this, we can integrate the health card to maintain medical records of all individuals and conduct awareness drives and campaigns. For ML classification models, we used decision tree classification and support vector classification algorithms for cervical cancer susceptibility and breast cancer susceptibility respectively. Thus, by devising this solution we come one step closer to our goal which is spreading cancer awareness, thereby, decreasing the cancer mortality and increasing cancer literacy among the people of Telangana.
format Preprint
id arxiv_https___arxiv_org_abs_2506_21500
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Devising a solution to the problems of Cancer awareness in Telangana
Avhad, Priyanka
Kshirsagar, Vedanti
Ranjan, Urvi
Nakhua, Mahek
Machine Learning
Computers and Society
Quantitative Methods
According to the data, the percent of women who underwent screening for cervical cancer, breast and oral cancer in Telangana in the year 2020 was 3.3 percent, 0.3 percent and 2.3 percent respectively. Although early detection is the only way to reduce morbidity and mortality, people have very low awareness about cervical and breast cancer signs and symptoms and screening practices. We developed an ML classification model to predict if a person is susceptible to breast or cervical cancer based on demographic factors. We devised a system to provide suggestions for the nearest hospital or Cancer treatment centres based on the users location or address. In addition to this, we can integrate the health card to maintain medical records of all individuals and conduct awareness drives and campaigns. For ML classification models, we used decision tree classification and support vector classification algorithms for cervical cancer susceptibility and breast cancer susceptibility respectively. Thus, by devising this solution we come one step closer to our goal which is spreading cancer awareness, thereby, decreasing the cancer mortality and increasing cancer literacy among the people of Telangana.
title Devising a solution to the problems of Cancer awareness in Telangana
topic Machine Learning
Computers and Society
Quantitative Methods
url https://arxiv.org/abs/2506.21500