标题： 设计解决特伦甘纳邦癌症意识问题的方案 显示英文标题

标题： Devising a solution to the problems of Cancer awareness in Telangana

摘要： 根据数据，2020年特伦甘纳邦接受宫颈癌、乳腺癌和口腔癌筛查的女性百分比分别为3.3%、0.3%和2.3%。 尽管早期检测是减少发病率和死亡率的唯一方法，但人们对宫颈癌和乳腺癌的症状和体征以及筛查实践的认识却非常低。 我们开发了一个机器学习分类模型，根据人口统计因素预测一个人是否容易患乳腺癌或宫颈癌。 我们设计了一个系统，可以根据用户的地理位置或地址提供最近医院或癌症治疗中心的建议。 此外，我们可以将健康卡进行整合，以维护所有个人的医疗记录，并开展宣传和宣传活动。 对于机器学习分类模型，我们分别使用了决策树分类和支持向量分类算法来预测宫颈癌和乳腺癌的易感性。 因此，通过设计这个解决方案，我们向我们的目标又迈进了一步，即传播癌症意识，从而降低特伦甘纳邦的癌症死亡率并提高人们的癌症知识水平。 显示英文摘要

摘要： 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.