Vol. 3 No. 2 (2023): Journal of Deep Learning in Genomic Data Analysis
Articles

Human-Centric Design of AI-driven Clinical Decision Support Systems: Designs AI-driven clinical decision support systems with a focus on user-centered design principles to enhance usability and adoption

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  • Dr. Kimiko Tanaka
Dr. Kimiko Tanaka
Professor of Computer Science, Waseda University, Japan
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Published 20-12-2023

Keywords

  • Clinical Decision Support Systems,
  • Human-Centric Design,
  • Patient Outcomes
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Kimiko Tanaka, “Human-Centric Design of AI-driven Clinical Decision Support Systems: Designs AI-driven clinical decision support systems with a focus on user-centered design principles to enhance usability and adoption”, Journal of Deep Learning in Genomic Data Analysis, vol. 3, no. 2, pp. 24–34, Dec. 2023, Accessed: Nov. 13, 2024. [Online]. Available: https://thelifescience.org/index.php/jdlgda/article/view/47

Abstract

This research paper explores the critical role of human-centric design in the development of AI-driven Clinical Decision Support Systems (CDSS). With the increasing complexity of healthcare systems and the growing volume of clinical data, AI has emerged as a valuable tool to assist healthcare professionals in making informed decisions. However, the effectiveness of AI-driven CDSS depends not only on the accuracy of the underlying algorithms but also on how well these systems are designed to fit into the workflow and decision-making processes of healthcare providers. This paper discusses the key principles of human-centric design and presents a framework for designing AI-driven CDSS that prioritize user needs and preferences. By incorporating human-centric design principles into the development process, AI-driven CDSS can enhance usability, increase acceptance among healthcare professionals, and ultimately improve patient outcomes.

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