Generative Medical Artificial Intelligence in Medical Imaging and Radiation Therapy: Enhancing Diagnosis, Workflow, And Patient Care for Effective Health Outcomes
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Date
2024-11-25
Authors
Aleruchi Chuku
Emmanuel I. Richard
Dlama J. Zira
Ibrahim S. Osanga
Alexander Monday
Abdulganiyu Salami
Ibitomisin S. Femi
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Publisher
MIRG
Abstract
Artificial intelligence (AI) is an umbrella term that explain the Creating computer systems that can do things that normally need human intelligence. AI technologies have already begun transforming clinical practice across various healthcare sectors. AI's applications in medical imaging, such as enhancing diagnostic precision and workflow efficiency is influencing and reshaping radiology departments worldwide. Medical imaging is central to modern healthcare, providing essential insights into disease detection, diagnosis, and treatment planning.
Objectives: The primary objective is to determine the rapid integration of AI is changing the practice of medical imaging in clinical settings. The focus is on the impact AI has on diagnosis, workflow, and patient care, ultimately leading to improved health outcomes.
Method: This paper systematically reviews the latest AI innovations in medical imaging, focusing on applications in diagnostic accuracy, efficiency improvements, and therapeutic personalization. Secondary sources of data from related and relevant literatures and articles were gathered using academic databases such as Google Scholar, ScienceDirect, Springer, and PubMed. The search terms used included: "AI and Radiographers' practice," "AI and Radiography," "Impact of AI on Radiography practice," "AI and Medical Imaging," and "Impact of AI on Medical Imaging." PRISMA guideline was used to synthesize the articles.
Results: Out of a total of 37 articles downloaded, 11 were found to be relevant and directly related to the study's topic and objectives. The review revealed that AI is already making a significant impact in radiation medicine, particularly by improving diagnostic accuracy, streamlining workflows, and enhancing patient care. Radiologist and Radiographers expressed a generally positive attitude toward the integration of AI, recognizing its potential to improve clinical outcomes.
Conclusion: Radiology professionals see great potential in incorporating AI, which promise to drive the growth of medical imaging and improve healthcare delivery. The integration of AI is expected to lead to increased cross-modality education, expanded technological expertise, and broader responsibilities. However, the successful integration of AI requires appropriate training programs, transparent policies, and a strong emphasis on maintaining patient-centered compassionate care in practice.
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Citation
Aleruchi C., Emmanuel I. R., Dlama J. Z., Ibrahim S. O., Alexander M., Abdulganiyu S. & Ibitomisin S. F. (2024). “Generative Medical Artificial Intelligence in Medical Imaging and Radiation Therapy: Enhancing Diagnosis, Workflow, And Patient Care for Effective Health Outcomes". In Proceedings of the International Conference on Artificial Intelligence and Robotics (MIRG-ICAIR 2024), pp. 181-190, MIRG