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Cancer Prognosis Using Artificial Intelligence-Based Techniques by Surbhi Gupta; Yogesh Kumar is a Computer Science article available to read on EtoBox.

What is Cancer Prognosis Using Artificial Intelligence-Based Techniques about?

Cancer is one of the most dreadful causes of destruction to mankind. Many bioinformatics investigators have applied Artificial Intelligence (AI)-based learning approaches with the aim to develop computationally efficient models for detection of cancerous conditions. Gene expression analysis has shown significant promise in predicting outcomes for several kinds of cancer. Nonetheless, limited sample sizes continue to be a barrier to developing strong and effective classifiers. Traditional supervised learning approaches are limited to labeled data. As a result, a substantial proportion of microarray data sets that lack appropriate follow-up information are ignored. Ability of AI-based deep learning strategies to perceive noteworthy features from intricate datasets exposes their significance. Artificial intelligence and machine learning techniques are making inroads into biological research and health care, including, crucially, cancer research and the healthcare sector, where its practical implications are immense. These include cancer detection and diagnosis, subtype categorization, cancer therapy optimization, and the identification of novel therapeutic pathways in pharmaceutical r

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Author

Surbhi Gupta; Yogesh Kumar

Publisher

Springer Science and Business Media LLC

Published

2021

Language

EN

Field

Computer Science (Physical Sciences)