The knowledge of radiological technologists is expected to increase with medical development. However, it is impossible to impart all knowledge in a limited time frame. Problem-based learning (PBL) is a learning methodology to solve it. In the PBL, students can gain problem-solving abilities by acquiring necessary knowledge from clinical cases and applying them during practice. We here report to implement the PBL in radiography practice. This practice opened a course at 2nd semester of third-grade students in our school. The practice flow includes presentation of clinical case and a survey of necessary knowledge, group work, radiography, reflection through practice, and deliberation of different cases. The clinical case was the radiography of an emergency patient. The evaluation items were about knowledge, skill, and attitude. By the PBL practice, students could realize a clinical scene, and discover considerable points unwritten in textbooks.
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http://dx.doi.org/10.6009/jjrt.2015_JSRT_71.3.216 | DOI Listing |
Bioinform Biol Insights
January 2025
Department of Pathology & Clinical Bioinformatics, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
While deep learning (DL) is used in patients' outcome predictions, the insufficiency of patient samples limits the accuracy. In this study, we investigated how transfer learning (TL) alleviates the small sample size problem. A 2-step TL framework was constructed for a difficult task: predicting the response of the drug temozolomide (TMZ) in glioblastoma (GBM) cell cultures.
View Article and Find Full Text PDFSci Rep
January 2025
Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea.
Model optimization is a problem of great concern and challenge for developing an image classification model. In image classification, selecting the appropriate hyperparameters can substantially boost the model's ability to learn intricate patterns and features from complex image data. Hyperparameter optimization helps to prevent overfitting by finding the right balance between complexity and generalization of a model.
View Article and Find Full Text PDFMed Sci Educ
June 2024
Medicolegal Institute, Ibn Rochd University Hospital,, Casablanca, Morocco.
Background: This scoping review aimed to explore the existing literature on teaching clinical reasoning in the field of forensic medicine.
Methods: The scoping review was conducted following the PRISMA extension for scoping reviews.
Results: The initial search yielded a total of 98 articles, of which 40 studies met the inclusion criteria.
Front Neuroinform
December 2024
Institute of Theoretical Physics, Jagiellonian University, Kraków, Poland.
Understanding brain function relies on identifying spatiotemporal patterns in brain activity. In recent years, machine learning methods have been widely used to detect connections between regions of interest (ROIs) involved in cognitive functions, as measured by the fMRI technique. However, it's essential to match the type of learning method to the problem type, and extracting the information about the most important ROI connections might be challenging.
View Article and Find Full Text PDFDiscov Med (Cham)
December 2024
Department of Engineering in the Faculty of Science, Thompson Rivers University, 805 TRU Way, Kamloops, BC V2C 0C8 Canada.
Cardiovascular diseases are a major cause of mortality and morbidity. Fast detection of life-threatening emergency events and an earlier start of the therapy would save many lives and reduce successive disabilities. Understanding the specific risk factors associated with heart attack and the degree of association is crucial in the clinical diagnosis.
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