Analytics, Free Full-Text

Por um escritor misterioso
Last updated 23 dezembro 2024
Analytics, Free Full-Text
Introduction: Prostate cancer (PCa) is one of the deadliest and most common causes of malignancy and death in men worldwide, with a higher prevalence and mortality in developing countries specifically. Factors such as age, family history, race and certain genetic mutations are some of the factors contributing to the occurrence of PCa in men. Recent advances in technology and algorithms gave rise to the computer-aided diagnosis (CAD) of PCa. With the availability of medical image datasets and emerging trends in state-of-the-art machine and deep learning techniques, there has been a growth in recent related publications. Materials and Methods: In this study, we present a systematic review of PCa diagnosis with medical images using machine learning and deep learning techniques. We conducted a thorough review of the relevant studies indexed in four databases (IEEE, PubMed, Springer and ScienceDirect) using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. With well-defined search terms, a total of 608 articles were identified, and 77 met the final inclusion criteria. The key elements in the included papers are presented and conclusions are drawn from them. Results: The findings show that the United States has the most research in PCa diagnosis with machine learning, Magnetic Resonance Images are the most used datasets and transfer learning is the most used method of diagnosing PCa in recent times. In addition, some available PCa datasets and some key considerations for the choice of loss function in the deep learning models are presented. The limitations and lessons learnt are discussed, and some key recommendations are made. Conclusion: The discoveries and the conclusions of this work are organized so as to enable researchers in the same domain to use this work and make crucial implementation decisions.
Analytics, Free Full-Text
Free Download Digital Analytics for Marketing Full Pages by
Analytics, Free Full-Text
32 Instagram Analytics Tools To Try In 2023
Analytics, Free Full-Text
6 Techniques Of Data Analytics : Free Download, Borrow, and
Analytics, Free Full-Text
Free web analytics with full session replays
Analytics, Free Full-Text
Web Analytics, Customer journey analytics
Analytics, Free Full-Text
FREE Data Analytics FREE Program, Python, Day-6
Analytics, Free Full-Text
I Wrote an Open Source Analytics Platform in full Javascript in
Analytics, Free Full-Text
Information, Free Full-Text
Analytics, Free Full-Text
Google Analytics vs Piwik Pro
Analytics, Free Full-Text
Dimensions - free version
Analytics, Free Full-Text
Mohan Nayak on LinkedIn: #dataanalytics #learning

© 2014-2024 progresstn.com. All rights reserved.