Africa’s readiness for artificial intelligence in clinical radiotherapy delivery: Medical physicists to lead the way
Date
2023
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Physica Medica
Abstract
Background: There have been several proposals by researchers for the introduction of Artificial Intelligence (AI)
technology due to its promising role in radiotherapy practice. However, prior to the introduction of the tech nology, there are certain general recommendations that must be achieved. Also, the current challenges of AI must
be addressed. In this review, we assess how Africa is prepared for the integration of AI technology into radio therapy service delivery.
Methods: To assess the readiness of Africa for integration of AI in radiotherapy services delivery, a narrative
review of the available literature from PubMed, Science Direct, Google Scholar, and Scopus was conducted in the
English language using search terms such as Artificial Intelligence, Radiotherapy in Africa, Machine Learning,
Deep Learning, and Quality Assurance.
Results: We identified a number of issues that could limit the successful integration of AI technology into
radiotherapy practice. The major issues include insufficient data for training and validation of AI models, lack of
educational curriculum for AI radiotherapy-related courses, no/limited AI teaching professionals, funding, and
lack of AI technology and resources. Solutions identified to facilitate smooth implementation of the technology
into radiotherapy practices within the region include: creating an accessible national data bank, integrating AI
radiotherapy training programs into Africa’s educational curriculum, investing in AI technology and resources
such as electronic health records and cloud storage, and creation of legal laws and policies to support the use of
the technology. These identified solutions need to be implemented on the background of creating awareness
among health workers within the radiotherapy space.
Conclusion: The challenges identified in this review are common among all the geographical regions in the Af rican continent. Therefore, all institutions offering radiotherapy education and training programs, management
of the medical centers for radiotherapy and oncology, national and regional professional bodies for medical
physics, ministries of health, governments, and relevant stakeholders must take keen interest and work together
to achieve this goal.
Description
Research Article
Keywords
Artificial intelligence, Radiotherapy, Machine learning, Deep learning