Devising a solution to the problems of Cancer awareness in Telangana

TL;DR

This paper presents a machine learning-based system to predict cancer susceptibility and improve awareness in Telangana, aiming to enhance early detection and reduce mortality rates.

Contribution

The study introduces a novel ML classification system combined with location-based hospital suggestions to promote cancer awareness and early detection in Telangana.

Findings

Decision tree used for cervical cancer susceptibility prediction.

Support vector machine used for breast cancer susceptibility prediction.

System facilitates access to nearby treatment centers and promotes awareness campaigns.

Abstract

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.