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

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.

Authors

Institutions

Publication Details

Journal
Journal of Ecohumanism
Published
2024-11-11
DOI
https://doi.org/10.62754/joe.v3i7.4668
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Mohsen Alyami, Fahad A. Al‐Harbi, Hussain Alyami, Mofleh Ali Alharbi et al.
3 citations
Journal of Ecohumanism
Artificial Intelligence in Healthcare and Education
0.36
article

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

Mohsen Alyami, Fahad A. Al‐Harbi, Hussain Alyami, Mofleh Ali Alharbi, Hamad Ali Muhammad Al Khuraim, Hadi Ali Mohammed Al, Khalid Ali Mohammed Albakri, Qubyl Nasser ALsaqran, Ahmed Saleh Alzamanan, AWADH MOHAMMAD SALEM AL SALEM
article en
3 citations

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.

Journal of EcohumanismVol. 3(7)
Ministry of Health (SA)
Openalex Percentile: Top 35%
Artificial Intelligence in Healthcare and Education
0.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Integrating Artificial Intelligence Across Medical Clinics: Strengthening Collaborative Efforts for Improved Patient Outcomes — Mohsen Alyami, Fahad A. Al‐Harbi, et al. · Journal of Ecohumanism (2024) | TGRS Research Map | TGRS