Authors:
Uchejeso Obeta, Dorcas Deko, and Eno Mantu
Addresses:
Department of Medical Laboratory Management, Federal College of Medical Laboratory Science & Technology, Jos, Plateau, Nigeria, uchejesoobeta@gmail.com, dekokemi@yahoo.com, eno_mantu@yahoo.com.
Deep learning excels at diagnosis and testing. Medical image-based cancer diagnosis is a deep learning (DL) application in machine learning and artificial intelligence that has been used in health care and medicine design. Medical, pathology, and imaging studies on cancer were scoping reviewed in this publication. It examined breast, rectal, and prostate cancer detection and testing in this era. Cancer patients benefit from prompt, accurate diagnosis, testing, and prediction. High computational resources have made DL a popular technology. CAD systems have preprocessing, feature recognition, extraction and selection, categorization, and performance assessment. Sequencing system cost reduction allows for accurate cancer diagnosis and prognosis prediction models. Current works show how DL has helped identify the best cancer diagnosis and prognosis models. DL is a generic model that works well with massive data sets and requires little data changes. The goals are to examine DL systems’ effects on histopathology images, summarise current DL approaches, and guide future researchers to increase their understanding and refine existing methods with deep learning models.
Keywords: Deep Learning (DL); Cancer and Medical Testing; Pathology and Medical Laboratory Science; 3d Model For Testing; Standard Computer-Aided Design (CAD); Breast Cancer.
Received on: 19/08/2023, Revised on: 03/11/2023, Accepted on: 29/11/2023, Published on: 07/03/2024
AVE Trends in Intelligent Health Letters, 2024 Vol. 1 No. 1, Pages: 28-37