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Background: Modernizing medical education by using artificial intelligence and other new technologies to improve the clinical thinking ability of medical students is an important research topic in recent years. Prominent medical universities are actively conducting research and exploration in this area. In particular, given the shortage of human resources, the need to maintain social distancing to prevent the spread of the epidemics, and the increase in the cost of medical education, it is critical to harness online learning to promote medical education. A virtual case learning system that uses natural language processing technology to process and present a hospital's real medical records and evaluate student responses can effectively improve medical students' clinical thinking abilities.Objective: The purpose of this study is to develop a virtual case system, AIteach, based on actual complete hospital medical records and natural language processing technology, and achieve clinical thinking ability improvement through a contactless, self-service, trial-and-error system application.Methods: Case extraction is performed on a hospital's case data center and the best-matching cases are produced through natural language processing, word segmentation, synonym conversion, and sorting. A standard clinical questioning data module, virtual case data module, and student learning difficulty module are established to achieve simulation. Students can view the objective examination and inspection data of actual cases, including details of the consultation and physical examination, and automatically provide their learning response via a multi-dimensional evaluation system. In order to assess the changes in students' clinical thinking after using AIteach, 15 medical graduate students were subjected to two simulation tests before and after learning through the virtual case system. The tests, which included the full-process case examination of cases having the same difficulty level, examined core clinical thinking test points such as consultation, physical examination, and disposal, and generated multi-dimensional evaluation indicators (rigor, logic, system, agility, and knowledge expansion). Thus, a complete and credible evaluation system is developed.Results: The AIteach system used an internal and external double-cycle learning model. Students collect case information through online inquiries, physical examinations, and other means, analyze the information for feedback verification, and generate their detailed multi-dimensional clinical thinking after learning. The feedback report can be evaluated and its knowledge gaps analyzed. Such learning based on real cases is in line with traditional methods of disease diagnosis and treatment, and addresses the practical difficulties in reflecting actual disease progression while keeping pace with recent research. Test results regarding short-term learning showed that the average score (P < 0.01) increased from 69.87 to 85.6, the five indicators of clinical thinking evaluation improved, and there was obvious logical improvement, reaching 47%.Conclusion: By combining real cases and natural language processing technology, AIteach can provide medical students (including undergraduates and postgraduates) with an online learning tool for clinical thinking training. Virtual case learning helps students to cultivate clinical thinking abilities even in the absence of clinical tutor, such as during pandemics or natural disasters. [ABSTRACT FROM AUTHOR]

Background: In the time of the coronavirus disease 2019 (COVID-19) pandemic, in-person lectures had to be shifted to online learning. This study aimed to evaluate students' and lecturers' perception and effectiveness of a virtual inverted classroom (VIC) concept on clinical radiology in comparison to a historic control. Methods: In the winter semester 2020/21, 136 fourth year medical students who completed the clinical radiology VIC during the pandemic, were included in the single centre, prospective study. Results were compared with a historic control that had finished the physical inverted classroom (PIC) in the immediately preceding year. The VIC consisted of an initial phase of self-determined preparation with learning videos and a second interactive phase of clinical case studies alternating between the virtual lecture hall and virtual buzz groups. At the end of the lecture series, students rated the lecture on a scale of 1 (most positive assessment) to 6 (most negative assessment) through an online survey platform. Additionally, they reported their impressions in free-form text. Lecturers were invited to comment on the VIC in a group interview. Main outcomes were final grades and student perception of the VIC. Results: Students' general impression of VIC was lower than that of PIC (median value of 3 [IQR 4, 2] and 1 [IQR 0, 0], p < 0.001), respectively, p < 0.001). The highest rating was achieved concerning use of the audience response system (median 1 [IQR 1, 0]), and the lowest concerning the buzz groups (median 4 [IQR 5, 3]). Students stated that they would have appreciated more details on reading images, greater focus on plenary case studies, and provision of exam related scripts. Lecturers would have liked better preparation by students, more activity of students, and stronger assistance for group support. Exam grades after VIC were better than after PIC (median 1 [IQR 2, 1] and 2 [IQR 2,1], respectively, p < 0.001). Conclusions: Students' overall perception of VIC was satisfactory, although worse than PIC. Final grades improved compared to PIC. Provided an adapted buzz group size and support, VIC may serve as complement in medical education once the pandemic is over. [ABSTRACT FROM AUTHOR]

Background: Practical courses in undergraduate medical training often lack a didactic concept. Active participation and learning success largely depend on chance. This study was initiated to evaluate a novel concept of structured work-based learning (WBL) in the course of students' half-day radiology immersion experience (IE). Methods: This prospective, single-centre cohort study included 228 third-year students of the 2019 summer semester who underwent the obligatory radiology IE at a university hospital. The course was based on a novel structured WBL concept that applied established didactic concepts including blended learning, the FAIR principles of feedback, activity, individualization, and relevance, and Peyton's four-step approach. Outcomes of equal weight were student and supervisor satisfaction with the clinical radiology IE assessed by paper-based- and online survey, respectively. Secondary outcome was achievement of intended learning outcomes assessed by means of mini clinical evaluation exercises and personal interviews. Results: Satisfaction with structured WBL was high in 99.0% of students. Students' expectations were exceeded, and they felt taken seriously at the professional level. Dissatisfaction was reasoned with quality of learning videos (0.6%), little support by supervisors (0.5%), or inadequate feedback (0.6%). Supervising resident physicians rated achievement of intended learning outcomes regarding cognitive and psychomotor competences as excellent for all students. Personal interviews revealed achievement of affective competence in some students. Twelve of 16 (75.0%) supervising physicians were satisfied with focussing on intended learning outcomes and student preparation for IE. Two of 15 (13.3%) supervisors were unsatisfied with time spent, and 4 of 16 (25%) with the approach of assessment. Conclusions: This study demonstrated that both students and supervisors were satisfied with the novel concept of structured WBL within the scope of clinical radiology IE. Achievement of intended learning outcomes was promising. [ABSTRACT FROM AUTHOR]