Litcius/Paper detail

A Study on Bladder Cancer Detection using AI-based Learning Techniques

Apeksha Koul, Yogesh Kumar, Anish Gupta

20222022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)16 citationsDOI

Abstract

Bladder cancer is currently the most frequent and worst cancer in the United States. Over the last several decades, bladder cancer detection and therapy breakthroughs have significantly reduced its mortality. Cystoscopy treatment has been considered useful for detecting and treating bladder cancer (BCa), but it is also prone to certain complications. Hence, this study has explored numerous research methodologies for identifying and diagnosing bladder cancer using AI techniques such as machine learning and deep learning models. The paper also emphasizes the accomplishments and challenges of researchers in this field. The assessment of the various techniques has also been compared to draw some conclusions.

Topics & Concepts

Bladder cancerCystoscopyCancerCancer detectionArtificial intelligenceMedicineComputer scienceDeep learningMachine learningMedical physicsPathologyInternal medicineAlternative medicineBladder and Urothelial Cancer TreatmentsColorectal Cancer Screening and Detection