This work is licensed under the Creative Commons Attribution 4.0 International License.
Henze, S. M., Fellmer, F., Wittenberg, S., et al. (2022). Digital adaptation of teaching disaster and deployment medicine under COVID-19 conditions: a comparative evaluation over 5 years. BMC Medical Education, 22(1), 1-9.Search in Google Scholar
Urbina-Fuentes, M., Jasso-Gutiérrez, L., Schiavon-Ermani, R., et al. (2017). [Transition from Millennium Development Goals to Sustainable Development Goals from the perspective of the social determinants of health and health equity]. Gaceta Medica De Mexico, 153(6), 697.Search in Google Scholar
Olayinka, O., Kekeh, M., Sheth-Chandra, M., et al. (2017). Big Data Knowledge in Global Health Education. Annals of Global Health, 83(3-4), 676-681.Search in Google Scholar
Hong, Q., Chen, et al. (2018). frontoparietal control network%mind wandering%moderating effect%positive affect%thought control ability. Frontiers in psychology, PP 2791.Search in Google Scholar
Sonia, Rahimi, Nathan C., et al. (2016). academic procrastination%attribution theory%blame%experimental philosophy%moral responsibility. Frontiers in psychology, PP 1179.Search in Google Scholar
Zapata, A., Men, C. H., et al. (2015). Evaluation and selection of group recommendation strategies for collaborative searching of learning objects. International Journal of Human-Computer Studies, 76, 22-39.Search in Google Scholar
Jones, A. C., Shipman, S. A., Ogrinc, G. (2015). Key characteristics of successful quality improvement curricula in physician education: a realist review. BMJ quality & safety, 24(1), 77-88.Search in Google Scholar
Lívia, Martins, Rossi, et al. (2019). [Crisis and mental health in adolescence: the story from the perspective of those who live it]. Cadernos De Saude Publica, PP e00125018.Search in Google Scholar
Willis, S. C., Astbury, J., Fenton, C., et al. (2022). Contribution of supervision to the development of advanced practitioners: a qualitative study of pharmacy learners’ and supervisors’ views. BMJ Open, 12(4), 37-46.Search in Google Scholar
Cmg, B., Edd, M., Kkb, B., et al. (2021). The other side of “challenging learners”: Strategies for teaching and precepting the overachiever and high performer. American Journal of Health-System Pharmacy, 79(2), 17-22.Search in Google Scholar
Envelope, M. T. B. A. P., A. F. Z., A. B. M., et al. (2022). The effect of decorative arts course on nursing students’ creativity and critical thinking dispositions. Nurse Education Today, 105584.Search in Google Scholar
Bork, F., Stratmann, L., Enssle, S., et al. (2019). The Benefits of an Augmented Reality Magic Mirror System for Integrated Radiology Teaching in Gross Anatomy. Anatomical Sciences Education, 12(6), 585-598.Search in Google Scholar
Hjalmarson, M., Nelson, J. K., Holincheck, N., et al. (2022). Researchers as Coaches: Developing Mathematics Teaching Capacity Using MEAs for STEM Integration. Investigations in Mathematics Learning, 14(1), 28-48.Search in Google Scholar
Fagerstrom, J. M., Wendy, et al. (2019). A hands-on introduction to medical physics and radiation therapy for middle school students. Journal of applied clinical medical physics, 20(4), 148-153.Search in Google Scholar
Mulholland, M., McKenna, D., Lewis, J. (2021). ‘I’m too busy to teach’. Tips for teaching when time is tight. Archives of disease in childhood - Education And practice edition, 159(N), 631-5.Search in Google Scholar
Rozenshtein, A., Gregory, et al. (2016). Effect of Massed Versus Interleaved Teaching Method on Performance of Students in Radiology. Journal of the American College of Radiology.Search in Google Scholar
Ahn, S., Nam, et al. (2018). [Patient Safety Teaching Competency of Nursing Faculty]. Journal of Korean Academy of Nursing, 48(6), 720-730.Search in Google Scholar
Parra, D., Brusilovsky, P. (2015). User-controllable personalization: A case study with SetFusion. International Journal of Human-Computer Studies, 78, 43-67.Search in Google Scholar
Hongbo, Y. U., Wang, G., Cao, Q., et al. (2015). A Fusion Based Particle Filter TBD Algorithm for Dim Targets. Chinese Journal of Electronics, 24(3), 590-595.Search in Google Scholar
Liu, X., Xu, Y., Cheng, Y., et al. (2018). A heterogeneous information fusion deep reinforcement learning for intelligent frequency selection of HF communication. China Communications, 15(9), 73-84.Search in Google Scholar
Khattab, A. A., Algergawy, A., Sarhan, A. (2015). A sequence-based tree similarity search. Knowledge-Based Systems, 85, 245-255.Search in Google Scholar
Czekaj, L., Przysiężna, A., Horodecki, M., et al. (2015). Quantum metrology: Heisenberg limit with bound entanglement. Physical Review A, 92(6), 062303.Search in Google Scholar
Jenke, R., Peer, A., Buss, M. (2017). Feature Extraction and Selection for Emotion Recognition from EEG. IEEE Transactions on Affective Computing, 5(3), 327-339.Search in Google Scholar
Galar, M., Derrac, J., Peralta, D., et al. (2015). A survey of fingerprint classification Part I: Taxonomies on feature extraction methods and learning models. Knowledge-based systems, 81, 76-97.Search in Google Scholar
Huang, Y., Xiao, et al. (2018). Intrinsic feature extraction using discriminant diffusion mapping analysis for automated tool wear evaluation. Frontiers of Information Technology & Electronic Engineering, 19(11), 1352-1361.Search in Google Scholar
Zhuang, Zhang, Jie, et al. (2019). Application of tabu search-based Bayesian networks in exploring related factors of liver cirrhosis complicated with hepatic encephalopathy and disease identification. Scientific Reports, 9(1), 1-8.Search in Google Scholar
Revealing the determinants of wheat yields in the Siberian breadbasket of Russia with Bayesian networks. (2019). Chinese Chemical Letters, 80, 21-31.Search in Google Scholar
Sánchez, Y. G., Sabir, Z., Guirao, J. L. G. (2020). Design of a nonlinear SITR fractal model based on the dynamics of a novel coronavirus (COVID-19). Fractals, 28(08), 2040026.Search in Google Scholar