A comprehensive assessment of artificial intelligence applications for cancer diagnosis
Gaurav Singh, Anushka Kamalja, Rohit Patil, Ashutosh Karwa, Akansha Tripathi, Pallavi Vijay Chavan
Abstract
Abstract Artificial intelligence (AI) is being used increasingly to detect fatal diseases such as cancer. The potential reduction in human error, rapid diagnosis, and consistency of judgment are the primary motives for using these applications. Artificial Neural Networks and Convolution Neural Networks are popular AI techniques being increasingly used in diagnosis. Numerous academics have explored and evaluated AI methods used in the detection of various cancer types for comparison and analysis. This study presents a thorough evaluation of the AI techniques used in cancer detection based on extensively researched studies and research trials published on the subject. The manuscript offers a thorough evaluation and comparison of the AI methods applied to the detection of five primary cancer types: breast cancer, lung cancer, colorectal cancer, prostate cancer, skin cancer, and digestive cancer. To determine how well these models compare with medical professionals’ judgments, the opinions of developed models and of experts are compared and provided in this paper.