Paper Info
Title
Recent Developments in Artificial Intelligence-Based Techniques for Prostate Cancer Detection - A Scoping Review.
Abstract
Artificial intelligence (AI) techniques can contribute to the early diagnosis of prostate cancer. Recently, there has been a sharp increase in the literature on AI techniques for prostate cancer diagnosis. This review article presents a summary of the AI methods that detect and diagnose prostate cancer using different medical imaging modalities. Following the PRISMA-ScR principle, this review covers 69 studies selected from 1441 searched papers 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 tissues that have prostate cancer. Most of the AI methods leveraged convolutional neural networks (CNNs) due to their ability to extract complex features. Some studies also reported traditional machine learning methods, such as support vector machines (SVM), decision trees for classification, LASSO, and Ridge regression methods for features extraction. We believe that the implementation of AI-based tools will support clinicians to provide better diagnosis plans for prostate cancer.
Year
DOI
Venue
2021
10.3233/SHTI210911
ICIMTH
Keywords
DocType
Volume
Prostate cancer,deep learning,machine learning,medical imaging
Conference
289
ISSN
Citations 
PageRank 
1879-8365
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Uzair Shah100.68
Md Rafuil Biswas200.34
Mahmood Saleh Alzubaidi300.34
Hazrat Ali401.35
Tanvir Alam502.03
Mowafa Househ603.04
Zubair Shah702.03