Enhancing Decision-Making in Public Health Informatics Using AI and Big Data Analytics

Renuka Jyothi.S, Zuleika Homavazir, Manoranjan Parhi, Nagireddy Mounika, Mithhil Arora, Akhilesh Kalia and Avir Sarkar

Seminars in Medical Writing and Education, 2024, vol. 3, 512

Abstract: In public health computing, artificial intelligence (AI) and big data analytics together provide a wealth of fresh approaches to handle significant public health issues, enhance patient outcomes, and guide choices. Standard approaches of analysis may fail to provide real-time insights that can be utilised to move fast as the volume of data in healthcare systems all across the globe rises. Together, artificial intelligence (AI) and big data analytics can manage enormous volumes of various kinds of health data, including social aspects of health, public health data, and electronic health records (EHR). This combination allows one to build prediction models able to detect emerging illnesses, see health trends approaching, and identify groups of persons at risk. From vast volumes of data, artificial intelligence systems—including deep learning and machine learning—can identify helpful patterns. This clarifies risk factors, forecasts disease outbreaks, and guides choices on the most efficient use of resources. Moreover, Big Data analytics allows us to examine large-scale effects of activities, thereby enabling individuals in decision-making to do so grounded on strong evidence. By anticipating how each patient will do, thus improving treatments, and so reducing variations in access to and outcomes of healthcare, using AI and Big Data combined may also assist to personalise healthcare. Using AI and Big Data in public health informatics presents some challenges even with these advances. Concerns concerning data security, the requirement of uniform data formats, and the possibility that algorithms may produce biassed choices abound, for instance. Dealing with these problems is very crucial if we are to guarantee fair and ethical use of Big Data and artificial intelligence to enhance public health choices. This article discusses how Big Data analytics and artificial intelligence will transform public health informatics going forward. It lists their advantages and drawbacks and offers ideas for improving the responses on the pitch.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:medicw:v:3:y:2024:i::p:512:id:512

DOI: 10.56294/mw2024512

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