The educational framework-Conceive, Design, Implement, and Operate-is part of an international proposal to improve education in the field of engineering, emphasizing how to teach engineering comprehensively, which allows the standardization of skills in professionals as a model for teaching engineering. Moreover, problem-based learning allows students to experiment with challenging situations through cases that simulate natural contexts with their profession. The integration of these two education strategies applied to the Internet of Things (IoT) Education for Industry 4.0 has promoted the generation of teaching challenges. Our education strategy proposes the synergy between laboratory guides and the classroom with the following actions: the content of the topic is presented, followed by the presentation of an issue focused into a realistic context, with practical exercises integrating software and hardware for the deployment of the solution to be reported as a final project. Moreover, undergraduate students in the biomedical engineering area acquired new knowledge about IoT, but at the same time, they may develop skills in the field of programming and structuring different architectures to solve real-world problems. Finally, traditional models of education require new teaching initiatives in the field of biomedical engineering concerning the current challenges and needs of the labor market.
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http://dx.doi.org/10.3390/s22228979 | 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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