A Review on Explainable Artificial Intelligence in Colorectal Cancer Biomarker Analysis using Microbiome Data

Abstract

In recent years, the potential to enhance colon cancer detection, prediction, and overall patient care has generated significant interest in integrating artificial intelligence (AI) into healthcare. The use of AI can improve the decision-making process in the field of medical illnesses such as colon cancer. Explainable artificial intelligence (XAI) has improved the interpretability and transparency of in-depth analyses of diseases. This study helps us to understand the deep concern related to colon cancer by utilizing explainable AI for detection and prediction. The major areas of conclusion are early detection after the screening, finding the associated risk, and final decision-making. This review highlights the advantages and disadvantages of the earlier proposed literature reviews by employing XAI for prognosis and Diagnosis. Furthermore, it discusses the challenges associated with and future research that can be made out of it. The ethical and legal consideration of colon cancer is also examined in the article. So, the proposed review of the explainable artificial intelligence can help develop clinical implications and enhance education for improved colon cancer care and its results.

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