Improving the quality of optimisation studies undertaken in mammography and general radiology using high level blended teaching

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Abstract

The EU funded project EUtempe-RX to develop 12 modules for training of medical physics experts (MPEs) in diagnostic and interventional radiology. Each course module provided 80 h of blended learning (a mixture of online and face-to-face training). The effectiveness of high-level blended learning for training MPEs up to EQF level 8 was tested on optimisation in mammography and general radiology. The training methods were evaluated using a questionnaire (89% response rate) and reviewing participants’ proposed optimisation studies. The online training was the most highly rated part of the module. The participants produced a wide range of feasible and interesting optimisation proposals. All questionnaire responders intend to undertake their study. Overall, the proposals showed a good understanding of the process of optimisation, but some showed weaknesses in applying the results clinically. The blended learning approach showed potential for training MPEs to undertake successful optimisation projects.

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Mackenzie, A., Young, K. C., Creten, S., Van Peteghem, N., & Bosmans, H. (2016). Improving the quality of optimisation studies undertaken in mammography and general radiology using high level blended teaching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9699, pp. 75–82). Springer Verlag. https://doi.org/10.1007/978-3-319-41546-8_10

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