Objectives Radiologists’ perception is likely to influence the adoption of artificial intelligence (AI) into clinical practice. We investigated knowledge and attitude towards AI by radiologists and residents in Europe and beyond. Methods Between April and July 2019, a survey on fear of replacement, knowledge, and attitude towards AI was accessible to radiologists and residents. The survey was distributed through several radiological societies, author networks, and social media. Independent predictors of fear of replacement and a positive attitude towards AI were assessed using multivariable logistic regression. Results The survey was completed by 1,041 respondents from 54 mostly European countries. Most respondents were male (n = 670, 65%), median age was 38 (24–74) years, n = 142 (35%) residents, and n = 471 (45%) worked in an academic center. Basic AI-specific knowledge was associated with fear (adjusted OR 1.56, 95% CI 1.10–2.21, p = 0.01), while intermediate AI-specific knowledge (adjusted OR 0.40, 95% CI 0.20–0.80, p = 0.01) or advanced AI-specific knowledge (adjusted OR 0.43, 95% CI 0.21–0.90, p = 0.03) was inversely associated with fear. A positive attitude towards AI was observed in 48% (n = 501) and was associated with only having heard of AI, intermediate (adjusted OR 11.65, 95% CI 4.25–31.92, p < 0.001), or advanced AI-specific knowledge (adjusted OR 17.65, 95% CI 6.16–50.54, p < 0.001). Conclusions Limited AI-specific knowledge levels among radiology residents and radiologists are associated with fear, while intermediate to advanced AI-specific knowledge levels are associated with a positive attitude towards AI. Additional training may therefore improve clinical adoption. Key Points • Forty-eight percent of radiologists and residents have an open and proactive attitude towards artificial intelligence (AI), while 38% fear of replacement by AI. • Intermediate and advanced AI-specific knowledge levels may enhance adoption of AI in clinical practice, while rudimentary knowledge levels appear to be inhibitive. • AI should be incorporated in radiology training curricula to help facilitate its clinical adoption.

Key Results 1. A model using baseline patient characteristics, laboratory markers, and chest radiography can predict short-term critical illness in hospitalized patients with COVID-19, with an internally validated AUC = 0.77. 2. At an example model risk threshold of 0.70, 71 of 356 patients would be predicted to develop critical illness of which 59 (83%) would be true-positives. 3. A risk calculator has been made available for download: Dutch COVID-19 risk model (https://docs.google.com/spreadsheets/d/1eFrdHxnOA-M_P-ijxnC2u30qk7IhMVV6YvHvJhrZ8Ws/edit#gid=0) (see Appendix E2).

BackgroundMagnetic resonance-guided high intensity focused ultrasound (MR-HIFU) has recently emerged as an effective treatment option for painful bone metastases. We describe here the first experience with volumetric MR-HIFU for palliative treatment of painful bone metastases and evaluate the technique on three levels: technical feasibility, safety, and initial effectiveness.MethodsIn this observational cohort study, 11 consecutive patients (7 male and 4 female; median age, 60 years; age range, 53–86 years) underwent 13 treatments for 12 bone metastases. All patients exhibited persistent metastatic bone pain refractory to the standard of care. Patients were asked to rate their worst pain on an 11-point pain scale before treatment, 3 days after treatment, and 1 month after treatment. Complications were monitored. All data were prospectively recorded in the context of routine clinical care. Response was defined as a ≥2-point decrease in pain at the treated site without increase in analgesic intake. Baseline pain scores were compared to pain scores at 3 days and 1 month using the Wilcoxon signed-rank test. For reporting, the STROBE guidelines were followed.ResultsNo treatment-related major adverse events were observed. At 3 days after volumetric MR-HIFU ablation, pain scores decreased significantly (p = 0.045) and response was observed in a 6/11 (55%) patients. At 1-month follow-up, which was available for nine patients, pain scores decreased significantly compared to baseline (p = 0.028) and 6/9 patients obtained pain response (overall response rate 67% (95% confidence interval (CI) 35%–88%)).ConclusionsThis is the first study reporting on the volumetric MR-HIFU ablation for painful bone metastases. No major treatment-related adverse events were observed during follow-up. The results of our study showed that volumetric MR-HIFU ablation for painful bone metastases is technically feasible and can induce pain relief in patients with metastatic bone pain refractory to the standard of care. Future research should be aimed at standardization of the treatment procedures and treatment of larger numbers of patients to assess treatment effectiveness and comparison to the standard of care.

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Background The coronavirus disease 2019 (COVID-19) pandemic led to far-reaching restrictions of social and professional life, affecting societies all over the world. To contain the virus, medical schools had to restructure their curriculum by switching to online learning. However, only few medical schools had implemented such novel learning concepts. We aimed to evaluate students’ attitudes to online learning to provide a broad scientific basis to guide future development of medical education. Methods Overall, 3286 medical students from 12 different countries participated in this cross-sectional, web-based study investigating various aspects of online learning in medical education. On a 7-point Likert scale, participants rated the online learning situation during the pandemic at their medical schools, technical and social aspects, and the current and future role of online learning in medical education. Results The majority of medical schools managed the rapid switch to online learning (78%) and most students were satisfied with the quantity (67%) and quality (62%) of the courses. Online learning provided greater flexibility (84%) and led to unchanged or even higher attendance of courses (70%). Possible downsides included motivational problems (42%), insufficient possibilities for interaction with fellow students (67%) and thus the risk of social isolation (64%). The vast majority felt comfortable using the software solutions (80%). Most were convinced that medical education lags behind current capabilities regarding online learning (78%) and estimated the proportion of online learning before the pandemic at only 14%. In order to improve the current curriculum, they wish for a more balanced ratio with at least 40% of online teaching compared to on-site teaching. Conclusion This study demonstrates the positive attitude of medical students towards online learning. Furthermore, it reveals a considerable discrepancy between what students demand and what the curriculum offers. Thus, the COVID-19 pandemic might be the long-awaited catalyst for a new “online era” in medical education.