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ISSN 2063-5346
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EXPLORING AI-BASED HUMAN-CENTERED DATA ANALYSIS METHODS IN CHEMISTRY: A COMPREHENSIVE REVIEW

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Anil Saroliya,Dinesh Mendhe,Dr. Tasneem K. H. Khan,Dr. Ahmad Jamal,Dr. P. Jacquline Rosy,S. D. Ajagekar,Hafiza Mamona Nazir,Dr. Trupti Dandekar Humnekar
» doi: 10.48047/ecb/2023.12.si5.103

Abstract

Artificial Intelligence (AI) systems for Data Analysis in Chemistry involves using AIbased models to analyze data related to chemistry and chemical substances. AI algorithms such as deep learning and machine learning can be used to classify chemical structures, predict properties and reactivity of new molecules, optimize existing synthetic pathways, and perform virtual screening. Additionally, AI models can be used to process large amounts of data quickly, identify and classify important features, and develop predictive models that enable efficient decision making. AI methods can be applied in a variety of contexts, from drug design and toxicity testing, to the discovery of new materials and chemicals. Data Analysis in Chemistry can be greatly enhanced by the use of Artificial Intelligence systems. AI algorithms such as deep learning and machine learning can be used to classify chemical structures, predict properties and reactivity of new molecules, optimize existing synthetic pathways, and perform virtual screening.

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