METHODS: This study employed a phenomenological design. Five focus groups were conducted with medical students who had participated in several Kahoot! sessions.
RESULTS: Thirty-six categories and nine sub-themes emerged from the focus group discussions. They were grouped into three themes: attractive learning tool, learning guidance and source of motivation.
CONCLUSIONS: The results suggest that Kahoot! sessions motivate students to study, to determine the subject matter that needs to be studied and to be aware of what they have learned. Thus, the platform is a promising tool for formative assessment in medical education.
METHODS: We propose to use Residual Blocks with a 3 × 3 kernel size for local feature extraction and Non-Local Blocks to extract the global features. The Non-Local Block has the ability to extract global features without using a huge number of parameters. The key idea behind the Non-Local Block is to apply matrix multiplications between features on the same feature maps.
RESULTS: We trained and validated the proposed method on the LIDC-IDRI dataset which contains 1018 computed tomography scans. We followed a rigorous procedure for experimental setup, namely tenfold cross-validation, and ignored the nodules that had been annotated by
APPROACH: Based on the principles of social learning, we combined speed mentoring and world café formats to offer a virtual Zoom™ workshop, with large and small group discussions, to reach health professions' educators across the globe. The goal was to establish a psychologically safe space for dialogue regarding adaptation to online teaching-learning formats.
EVALUATION: We aimed to establish psychological safety to stimulate thought-provoking discussions within the various small groups and obtain valuable contributions from participants. From these conversations, we were able to formulate 'hot tips' on how to adapt to (sometimes new) online teaching-learning formats while nurturing teacher and student wellbeing.
REFLECTION: Through this virtual workshop we realized that despite contextual differences, many challenges are common worldwide. We experienced technological difficulties during the session, which needed rapid adaptation by the organising team. We encouraged, but did not pressure, participants to use video and audio during breakout discussions as we wanted them to feel safe and comfortable. The large audience size and different time zones were challenging; therefore, leadership had to be resilient and focussed. Although this virtual format was triggered by the pandemic, the format can be continued in the future to discuss other relevant global education topics.
METHODS: In this study, we propose a multi-view secondary input residual (MV-SIR) convolutional neural network model for 3D lung nodule segmentation using the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) dataset of chest computed tomography (CT) images. Lung nodule cubes are prepared from the sample CT images. Further, from the axial, coronal, and sagittal perspectives, multi-view patches are generated with randomly selected voxels in the lung nodule cubes as centers. Our model consists of six submodels, which enable learning of 3D lung nodules sliced into three views of features; each submodel extracts voxel heterogeneity and shape heterogeneity features. We convert the segmentation of 3D lung nodules into voxel classification by inputting the multi-view patches into the model and determine whether the voxel points belong to the nodule. The structure of the secondary input residual submodel comprises a residual block followed by a secondary input module. We integrate the six submodels to classify whether voxel points belong to nodules, and then reconstruct the segmentation image.
RESULTS: The results of tests conducted using our model and comparison with other existing CNN models indicate that the MV-SIR model achieves excellent results in the 3D segmentation of pulmonary nodules, with a Dice coefficient of 0.926 and an average surface distance of 0.072.
CONCLUSION: our MV-SIR model can accurately perform 3D segmentation of lung nodules with the same segmentation accuracy as the U-net model.
OBJECTIVE: The aim of this study was to evaluate regular (4-hourly prior to each oral misoprostol dose with amniotomy when feasible) compared with restricted (only if indicated) vaginal assessments during labor induction with oral misoprostol in term nulliparous women MATERIALS AND METHODS: We performed a randomized trial between November 2016 and September 2017 in a university hospital in Malaysia. Our oral misoprostol labor induction regimen comprised 50 μg of misoprostol administered 4 hourly for up to 3 doses in the first 24 hours. Participants assigned to regular assessment had vaginal examinations before each 4-hourly misoprostol dose with a view to amniotomy as soon as it was feasible. Participants in the restricted arm had vaginal examinations only if indicated. Primary outcomes were patient satisfaction with the birth process (using an 11-point visual numerical rating scale), induction to vaginal delivery interval, and vaginal delivery rate at 24 hours.
RESULTS: Data from 204 participants (101 regular, 103 restricted) were analyzed. The patient satisfaction score with the birth process was as follows (median [interquartile range]): 7 [6-9] vs 8 [6-10], P = .15. The interval of induction to vaginal delivery (mean ± standard deviation) was 24.3 ± 12.8 vs 31.1 ± 15.0 hours (P = .013). The vaginal delivery rate at 24 hours was 27.7% vs 20.4%; (relative risk [RR], 1.4; 95% confidence interval [CI], 0.8-2.3; P = .14) for the regular vs restricted arms, respectively. The cesarean delivery rate was 50% vs 43% (RR, 1.1; 95% CI, 0.9-1.5; P = .36). When assessed after delivery, participants' fidelity to their assigned vaginal examination schedule in a future labor induction was 45% vs 88% (RR, 0.5; 95% CI, 0.4-0.7; P < .001), and they would recommend their assigned schedule to a friend (47% vs 87%; RR, 0.6; 95% CI, 0.5-0.7; P < .001) in the regular compared with the restricted arms, respectively.
CONCLUSION: Despite a shorter induction to vaginal delivery interval with regular vaginal examination and a similar vaginal delivery rate at 24 hours and birth process satisfaction score, women expressed a higher preference for the restricted examination schedule and were more likely to recommend such a schedule to a friend.