Keywords
implementation
How to Cite
Abstract
In modern healthcare, ensuring optimal clinical pathways and efficient care coordination are crucial for enhancing patient outcomes. This paper explores the application of artificial intelligence (AI) algorithms to optimize clinical pathways and improve care coordination processes. By leveraging AI, healthcare providers can streamline care delivery, reduce costs, and enhance patient experiences. This research examines various AI-powered solutions and their impact on clinical pathway optimization, highlighting key benefits and challenges. The paper concludes with recommendations for implementing AI-driven strategies to improve patient care coordination in healthcare settings.
References
Saeed, A., Zahoor, A., Husnain, A., & Gondal, R. M. (2024). Enhancing E-commerce furniture shopping with AR and AI-driven 3D modeling. International Journal of Science and Research Archive, 12(2), 040-046.
N. Pushadapu, “AI-Driven Solutions for Seamless Integration of FHIR in Healthcare Systems: Techniques, Tools, and Best Practices ”, Journal of AI in Healthcare and Medicine, vol. 3, no. 1, pp. 234–277, Jun. 2023
Chen, Jan-Jo, Ali Husnain, and Wei-Wei Cheng. "Exploring the Trade-Off Between Performance and Cost in Facial Recognition: Deep Learning Versus Traditional Computer Vision." Proceedings of SAI Intelligent Systems Conference. Cham: Springer Nature Switzerland, 2023.
Alomari, Ghaith, et al. “AI-Driven Integrated Hardware and Software Solution for EEG-Based Detection of Depression and Anxiety.” International Journal for Multidisciplinary Research, vol. 6, no. 3, May 2024, pp. 1–24.
Saeed, Ayesha, et al. "A Comparative Study of Cat Swarm Algorithm for Graph Coloring Problem: Convergence Analysis and Performance Evaluation." International Journal of Innovative Research in Computer Science & Technology 12.4 (2024): 1-9.