利用机器学习预测心血管疾病

K. Prajwal, Tharun K, N. P, M A.
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摘要

随着人口的增加,患病的机会也在增加。全球有许多疾病,当今医院系统面临的最大问题之一是缺乏技术来了解患者何时生病。其中一种疾病是心血管疾病(CVD)。它指的是任何心脏疾病、血管疾病或血管疾病。据世界卫生组织称,全世界死于心血管疾病的人比死于其他任何原因的人都多。它对低收入和中等收入国家的影响更大。独居的人生病时很难联系到医院。因此,我们开发了一种模型,可以检测到病人何时生病并向医院报告。目前,该系统只能识别患有心脏病的患者,并向医院报告。我们决定进行心脏病鉴定,因为它是最致命的疾病之一,患者死于心脏病的风险很高。预测病人是否患有心脏病显然是一个分类问题。因此,我们使用了五种模型进行分类。我们会考虑几个因素,比如血糖水平、年龄、胆固醇水平等等,然后根据输入给出结果。
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Cardiovascular Disease Prediction Using Machine Learning
As the human population increases, so is the chance of getting diseases. There are many illnesses globally, and one of the biggest problems faced by the hospital systems today is the lack of technology to know when the patients are ill. One such illness is Cardiovascular Disease or CVD. It refers to any heart disease, vascular disease, or blood vessel disease. According to WHO, more people die of CVD’s worldwide than any other cause. It affects the low and middle-income countries more. It is very hard for people living alone to contact the hospital when they are sick. Therefore, we have developed a model that can detect when a patient is ill and report back to the hospital. The system currently only identifies patients with heart disease and reports back to the hospital. We decided to go with heart disease identification because it is one of the most deadly diseases, and the risk of patients dying because of heart disease is high. Predicting whether a patient has heart disease or not is very clearly a classification problem. Therefore, we have used five models to classify. We take several factors such as blood sugar level, age, cholesterol level, and many more and give the outcome based on the input.
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