Recent developments in artificial intelligence-based prostate cancer detection techniques: A scoping review


This article was originally published here

Stud Health Technology Inform 14 Jan 2022;289:268-271. doi: 10.3233/SHTI210911.


Artificial intelligence (AI) techniques can help in the early detection of prostate cancer. Recently, the literature on AI techniques for prostate cancer diagnosis has proliferated. This review article presents a summary of AI methods that detect and diagnose prostate cancer using various medical imaging modalities. According to the PRISMA-ScR principle, this review includes 69 studies selected from 1441 searched articles published in the last three years. The application of AI methods reported in these articles can be divided into three broad categories: diagnosis, grading and segmentation of prostate cancer tissues. Most AI methods leverage Convolutional Neural Networks (CNNs) for their ability to extract complex features. Some studies also reported on traditional machine learning methods, such as B. Support Vector Machines (SVM), decision trees for classification, LASSO and ridge regression methods for feature extraction. We believe that the implementation of AI-based tools will help clinicians provide better prostate cancer diagnostic plans.

PMID:35062144 | DOI:10.3233/SHTI210911


Comments are closed.