Abstract
Automated examination of biomedical signals plays a vital role to diagnose diseases and offers useful data to several applications in the areas of physiology, sports medicine, and human-computer interface. The latest advancements in Artificial Intelligence (AI) have the ability to manage and analyse enormous biomedical datasets resulting in clinical decision making and real time applications. At the same time, Colorectal cancer (CRC) is the third most deadly disease affecting people over the globe. The utilization of AI techniques for the earlier identification of CRC has gained significant interest among the research communities. Therefore, this paper presents a novel AI based fusion model for CRC disease diagnosis and classification, named AIFM-CRC. The presented AIFM-CRC model primarily undergoes Gaussian filtering based noise removal and contrast enhancement as a preprocessing stage. In addition, a fusion based feature extraction process takes place where the SIFT based handcrafted features and Inception v4 based deep features are fused together. Besides, whale optimization algorithm tuned deep support vector machine model is employed as a classification technique to determine the existence of CRC. In order to highlight the proficient results analysis of the AIFM-CRC model, a comprehensive simulation analysis takes place. The resultant experimental values pointed out the betterment of the AIFM-CRC model by accomplishing a maximum accuracy of 96.18%.