Integrating Artificial Intelligence Across Medical Clinics: Strengthening Collaborative Efforts for Improved Patient Outcomes
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Keywords

Artificial Intelligence
Inter-clinic Collaboration
Healthcare Technology
Patient Outcomes
Predictive Analytics
Telemedicine
Medical Diagnostics
Data Sharing in Healthcare
Patient Management
Healthcare Interoperability

How to Cite

Alyami , M. S. M. ., Alyami , M. M. M. ., Khuraim , H. A. M. A. ., Alsalem, A. M. S. ., Alrayshan, H. A. M. ., Albakri, K. A. M. ., ALsaqran, Q. N. ., Alyami, H. S. ., Alzamanan , A. S. ., Alharbi , F. M., & Alharbi, M. A. . (2024). Integrating Artificial Intelligence Across Medical Clinics: Strengthening Collaborative Efforts for Improved Patient Outcomes. Journal of Ecohumanism, 3(7), 2691–2698. https://doi.org/10.62754/joe.v3i7.4668

Abstract

The integration of Artificial Intelligence (AI) across medical clinics holds transformative potential for enhancing patient outcomes through improved collaboration. This review examines the applications of AI in fostering inter-clinic connectivity, with a focus on diagnostics, treatment planning, and patient management. By utilizing AI-powered data-sharing platforms, predictive analytics, and telemedicine solutions, clinics can collaborate more efficiently, ensuring continuity of care and reducing diagnostic errors. Despite these advancements, challenges persist, including data privacy, interoperability, and resistance to AI adoption among clinical staff. This review highlights case studies showcasing successful AI-enabled collaborations and proposes future directions to address current limitations. Overall, AI's role in linking medical clinics underscores its potential to revolutionize patient care by bridging gaps in communication and decision-making processes.

https://doi.org/10.62754/joe.v3i7.4668
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