Publications by authors named "Ke-Yun Wang"
Chin Med Sci J
September 2022
Article Synopsis
- The study aimed to create a prostate cancer risk prediction model using common clinical indicators and evaluate AI technology's effectiveness in healthcare.
- After preparing the data and selecting features, the study applied various machine learning models (random forest, support vector machine, back propagation neural network, and convolutional neural network) to predict prostate cancer risk, identifying random forest as the most effective model.
- The research highlighted the significance of clinical indicators like inorganic phosphorus and triglycerides while developing an online tool for risk assessment, demonstrating the potential benefits of AI in enhancing medical diagnosis.
