HOW TO PREPARE FOR AI IN MEDICAL PHYSICS
DOI:
https://doi.org/10.17721/3041-1491/2024.11-02Keywords:
medical physics, artificial intelligence, imaging, therapy, quality assuranceAbstract
By increasing diagnostic precision, streamlining treatment regimens, and boosting patient outcomes, the incorporation of Artificial Intelligence (AI) into medical physics holds the potential to completely transform the healthcare industry. This short article examines the most recent developments and uses of artificial intelligence (AI) technologies, emphasizing on Imaging, Therapy, and Quality Assurance. As far as imaging is concerned the article elaborates mainly on the applications of AI in CT, MRI, and PET images, but also ultrasound, mammography, and radiography. Therapy is one field that needs AI more than any other, as this article explains. Finally the applications of AI in Quality Assurance, are excellent tools for the Medical Physicist (MP), and the reasons for this, are explained. Whether or not there are any risks associated with the clinical application of AI-based tools is examined and which risks these might be. Challenges and ethical considerations, which according to many researchers are of the utmost importance, are also examined briefly.
References
Avanzo, M., Trianni, T., Botta, F., Talamonti, C., Stasi, M., & Iori, M. (2021). Artificial Intelligence and the Medical Physicist: Welcome to the Machine. Appl. Sci., 11, 1691. https://doi.org/10.3390/app11041691
Bollmann, S., Kustner, T., Tao, Q., & Zoller, F. (2024, Mar 23). Artificial intelligence in medical physics. Z. Med Phys., 34(2), 177-178. https//doi.org/10.1016/j.zemedi.2024.03.002
DAIC. (2023). Revolutionizing Cardiology: AI-Based Technology Offers Accurate Analysis of Cardiac Disease. https://www.dicardiology.com/content/revolutionizing-cardiology-ai-based-technology- offers-accurate-analysis-cardiac-disease
Fortunati, V. (2022). Machine learning requires manual feature designing before the training of the algorithm can start. Deep learning combines feature extraction and the training of the algorithm using a neural network. https://www.quantib.com/blog/deep-learning-applications-in-radiology/classification
IAEA. (2023). Artificial Intelligence in Medical Physics, Series 83, Vienna, Austria.
Vision Research Reports. (2022). Artificial Intelligence (AI) in Radiology Market. https://www.visionresearchreports.com/artificial-intelligence-in-radiology-market/39342
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