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The Landscape of Artificial Intelligence Applications in Health Information Systems

by Frederick A. Adrah, Barbara E. Mottey, Hope Nyavor
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 23
Year of Publication: 2024
Authors: Frederick A. Adrah, Barbara E. Mottey, Hope Nyavor
10.5120/ijca2024923677

Frederick A. Adrah, Barbara E. Mottey, Hope Nyavor . The Landscape of Artificial Intelligence Applications in Health Information Systems. International Journal of Computer Applications. 186, 23 ( May 2024), 16-21. DOI=10.5120/ijca2024923677

@article{ 10.5120/ijca2024923677,
author = { Frederick A. Adrah, Barbara E. Mottey, Hope Nyavor },
title = { The Landscape of Artificial Intelligence Applications in Health Information Systems },
journal = { International Journal of Computer Applications },
issue_date = { May 2024 },
volume = { 186 },
number = { 23 },
month = { May },
year = { 2024 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number23/the-landscape-of-artificial-intelligence-applications-in-health-information-systems/ },
doi = { 10.5120/ijca2024923677 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-05-31T22:32:03.052282+05:30
%A Frederick A. Adrah
%A Barbara E. Mottey
%A Hope Nyavor
%T The Landscape of Artificial Intelligence Applications in Health Information Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 23
%P 16-21
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Artificial Intelligence, particularly Machine Learning, has become feasible thanks to the availability of big data, enhanced computing power and cloud storage across diverse sectors. In the realm of health information systems, these advancements continue to impact various sectors, including clinical decision support systems, AI-driven Chatbots, virtual assistants and predictive analytics for disease diagnosis and prognosis. AI helps in expediting image interpretation for medical professionals and is swiftly enhancing the efficiency of entire health systems. The introduction and utilization of AI not only mitigates costly errors but also empowers patients to leverage their data for improved health results. Hence, emphasizing ethics in AI is crucial for fostering trust and confidence. This necessitates thorough examination of issues like bias, privacy concerns, security and perceived transparency gaps. Therefore, further exploration of Fair Machine Learning, federated learning and Responsible AI is imperative. Most recently, the significance of AI applications in health information systems was particularly evident during the COVID-19 pandemic. Researchers anticipate substantial enhancements in the accuracy, productivity and workflow of AI applications over time. This conceptual paper provides an overview of the current and future trajectories of AI applications within the context of health information systems.

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Index Terms

Computer Science
Information Sciences
Artificial Intelligence
Deep Learning
Predictive analytics
Machine Learning
Health information systems

Keywords

Fair Machine Learning Responsible AI Federated Learning

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