Published 16-04-2024
Keywords
- AI,
- clinical decision support systems,
- evidence-based medicine,
- healthcare,
- artificial intelligence
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
Abstract
AI-Enabled Clinical Decision Support Systems (CDSS) have emerged as powerful tools to assist healthcare providers in making evidence-based medical decisions. These systems leverage artificial intelligence (AI) algorithms to analyze complex clinical data and provide recommendations that align with the best available evidence. This paper presents a comprehensive review of AI-enabled CDSS in the context of evidence-based medicine (EBM). We discuss the role of AI in improving clinical decision-making, the challenges and opportunities in developing these systems, and the potential impact on healthcare delivery. Additionally, we highlight key considerations for the successful implementation of AI-enabled CDSS in clinical practice.
Downloads
References
- Buddha, Govind Prasad, and Rahul Pulimamidi. "The Future Of Healthcare: Artificial Intelligence's Role In Smart Hospitals And Wearable Health Devices." Tuijin Jishu/Journal of Propulsion Technology 44.5 (2023): 2498-2504.
- Kolay, Srikanta, Kumar Sankar Ray, and Abhoy Chand Mondal. "K+ means: An enhancement over k-means clustering algorithm." arXiv preprint arXiv:1706.02949 (2017).
- Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.
- Dey, Sudipto, et al. "Methods and systems for selecting a machine learning algorithm." U.S. Patent Application No. 18/514,181.
- Pillai, Aravind Sasidharan. "Multi-label chest X-ray classification via deep learning." arXiv preprint arXiv:2211.14929 (2022).
- Dutta, Ashit Kumar, et al. "Deep learning-based multi-head self-attention model for human epilepsy identification from EEG signal for biomedical traits." Multimedia Tools and Applications (2024): 1-23.
- Raparthi, Mohan, Sarath Babu Dodda, and Srihari Maruthi. "AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health." European Economic Letters (EEL) 11.1 (2021).
- Pargaonkar, Shravan. "Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering." Journal of Science & Technology 1.1 (2020): 61-66.
- Venigandla, Kamala, and Venkata Manoj Tatikonda. "Improving Diagnostic Imaging Analysis with RPA and Deep Learning Technologies." Power System Technology 45.4 (2021).
- Reddy, Surendranadha Reddy Byrapu. "Ethical Considerations in AI and Data Science-Addressing Bias, Privacy, and Fairness." Australian Journal of Machine Learning Research & Applications 2.1 (2022): 1-12.
- Raparthi, Mohan, et al. "Advancements in Natural Language Processing-A Comprehensive Review of AI Techniques." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 1-10.