Diagnosis Model of Prostate Cancer Based on Machine Learning Algorithm

Prostate cancer is one of the most common malignant tumors in middle-aged and elderly men. Its incidence has been in the forefront of male malignant tumors, which has caused great harm to human health. How to predict prostate cancer patients and improve the diagnostic efficiency of prostate cancer has always been one of the key issues in the diagnosis of prostate cancer. In this paper, according to the collected data of patients, combined with medical guidelines and expert doctors ' advice, the data cleaning and statistical analysis were carried out, and 28 predictive variables were selected and extracted. These variables have been confirmed to have an impact on the occurrence of prostate cancer, and then a prostate cancer diagnosis model is established based on 4 machine learning methods. Finally, through the verification and evaluation of the model, the optimal prostate cancer diagnosis model is identified, the characteristics are further discussed, and the subsequent optimization suggestions of prostate cancer diagnosis model are given.