Teaching Methodologies
Seminars will be organised with national and international reference speakers who stand out in the areas under study.
The evaluation will be carried out through a report, with oral presentation and discussion, on one of the themes addressed at the student’s choice.
Learning Results
Knowledge:
– Innovative and differentiated knowledge of cutting-edge technology in medical imaging and radiotherapy
Skills:
– critical reasoning about the advantages of technological evolution and its future character
Competeneces:
– develop the perception of technology, risk and promotion of safety and quality
– insert in your professional activity the innovative character, maintaining good practices and deotological principles
Program
• Innovations in medical imaging and radiotherapy
• Artificial intelligence in the different areas of medical imaging and radiotherapy
• Different professional aspects in medical imaging and radiotherapy
Curricular Unit Teachers
Internship(s)
NAO
Bibliography
SarkarSiddiquea, James C.L.Chowbc, Artificial intelligence in radiotherapy, Volume 25, Issue 4, July–August 2020,
Pages 656-666, https://doi.org/10.1016/j.rpor.2020.03.015
Author: Katherine Colvin, Editorial Assistant, ARTIFICIAL INTELLIGENCE AND THE FUTURE OF RADIOGRAPHY, EMJ Radiol. 2020;1[1]:23-25.
Rani Ahmadorcid , The Role of Digital Technology and Artificial Intelligence in Diagnosing Medical Images: A
Systematic Review, Vol.11 No.1, March 2021
RobertSeifertMD*†‡§ManuelWeberMD†‡§EmreKocakavuk†‡§ChristophRischplerMD†‡§DavidKerstingMD, M.Sc.†‡§,
Artificial Intelligence and Machine Learning in Nuclear Medicine: Future Perspectives, , Volume 51, Issue 2, March
2021, Pages 170-177, https://doi.org/10.1053/j.semnuclmed.2020.08.003
van Timmeren, J., Cester, D., Tanadini-Lang, S. et al. Radiomics in medical imaging—“how-to” guide and critical
reflection. Insights Imaging 11, 91 (2020). https://doi.org/10.1186/s13244-020-00887-2