Artificial Intelligence (AI) is one of the biggest topics being discussed in the realm of Computer Science and it has made incredible breakthroughs possible in so many different industries. One of the largest issues with utilizing computational resources in the health industry historically is centered around the quantity of data, the specificity of conditions for accurate results, and the general risks associated with being incorrect in an analysis. Although these all have been major issues in the past, the application of artificial intelligence has opened up an entirely different realm of possibilities because accessing massive amounts of patient data, is essential for generating an extremely accurate model in machine learning (ML). This paper presents an analysis of tools and algorithm design techniques used in recent times to accelerate data processing in the realm of healthcare, but one of the most important discoveries is that the standardization of conditioned data being fed into the models is almost more important than the algorithms or tools being used combined.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.