Development of a face mask detection pipeline for mask-wearing monitoring in the era of the COVID-19 pandemic: A modular approach

During the SARS-Cov-2 pandemic, mask-wearing became an effective tool to prevent spreading and contracting the virus. The ability to monitor the mask-wearing rate in the population would be useful for determining public health strategies against the virus. However, artificial intelligence technologies for detecting face masks have not been deployed at a large scale in real-life to measure the mask-wearing rate in public. In this paper, we present a two-step face mask detection approach consisting of two separate modules: 1) face detection and alignment and 2) face mask classification. This approach allowed us to experiment with different combinations of face detection and face mask classification modules. More specifically, we experimented with PyramidKey and RetinaFace as face detectors while maintaining a lightweight backbone for the face mask classification module. Moreover, we also provide a relabeled annotation of the test set of the AIZOO dataset, where we rectified the incorrect labels for some face images. The evaluation results on the AIZOO and Moxa 3K datasets showed that the proposed face mask detection pipeline surpassed the state-of-the-art methods. The proposed pipeline also yielded a higher mAP on the relabeled test set of the AIZOO dataset than the original test set. Since we trained the proposed model using in-the-wild face images, we can successfully deploy our model to monitor the mask-wearing rate using public CCTV images.Comment: Accepted at the 19th International Joint Conference on Computer Science and Software Engineering (JCSSE 2022

Kümmell’s disease — uncommon or underreported disease: A clinicopathological account of a case and review of literature

Kümmell’s disease is a rare form of vertebral body osteonecrosis, which develops as a delayed post-traumatic event. It is infrequently reported in literature and to the best of our knowledge, has not been reported from India. We describe the clinical, radiological, and pathological features of a case occurring in a 60-year-old man and relevant brief review of the literature of this rare disease. Its close resemblance to more commonly occurring bony tuberculosis poses a diagnostic dilemma particularly in developing country like India, where tuberculosis is endemic. Awareness of this entity, though rare, is essential to avoid unnecessary diagnostic work up and treatment

Study protocol of a cluster randomized controlled trial to evaluate effectiveness of a system for maintaining high-quality early essential newborn care in Lao PDR

Abstract Background Reduction in neonatal deaths has been a major challenge globally. To prevent neonatal deaths, improvements in newborn care have been promoted worldwide. The World Health Organization Western Pacific Regional Office has been promoting the Early Essential Newborn Care (EENC), a package of specific simple and cost-effective interventions, in their region. However, mere introduction of EENC cannot reduce neonatal deaths unless quality of care is ensured. In Lao PDR, the government introduced self-managed continuous monitoring as a sustainable way to improve the quality of care described in the EENC. Methods A clustered randomized controlled trial was designed to compare the effectiveness of self-managed continuous monitoring with external supervisory visits to monitor health workers’ satisfactory EENC performance and their knowledge and skills related to the EENC in Lao PDR. Determinants of EENC performance will be measured with a structured questionnaire developed based on the Theory of Planned Behaviour, which predicts future behaviour. During self-managed continuous monitoring activities, health workers in each district hospital will conduct periodical peer reviews and feedback sessions. Fifteen district hospitals will be randomly allocated into the self-managed continuous monitoring (intervention) and the supervision (control) groups. Fifteen health workers routinely involved in maternity and newborn care including physicians, midwives and other health staff will be recruited from each hospital (effect size 0.6, intra-cluster correlation coefficient 0.06, 5% alpha error and 80% power). We will compare the change in the mean score of the determinants before and one year after randomisation between the two groups. We will also compare the retention of knowledge and skills related to the EENC between the two groups. The expected enrolment period is July 20th, 2017 to July 20th, 2018. Discussion This is the first cluster randomized trial to evaluate a self-managed continuous monitoring system for quality maintenance of newborn care in a resource-limited country. This research is conducted in collaboration with the Ministry of Health and international organizations; therefore, if effective, this intervention would be applied in larger areas of the country and the region. Trial registration This trial was registered at UMIN-CTR on 15th of June, 2017. Registration number is UMIN000027794

Additional file 2: of Study protocol of a cluster randomized controlled trial to evaluate effectiveness of a system for maintaining high-quality early essential newborn care in Lao PDR

Questionnaire on determinants to perform Early Essential Newborn Care. (DOCX 22 kb

Additional file 4: of Study protocol of a cluster randomized controlled trial to evaluate effectiveness of a system for maintaining high-quality early essential newborn care in Lao PDR

Simulation test on Early Essential Newborn Care. (DOCX 24 kb

Additional file 3: of Study protocol of a cluster randomized controlled trial to evaluate effectiveness of a system for maintaining high-quality early essential newborn care in Lao PDR

Written test on Early Essential Newborn Care. (PDF 1653 kb

Additional file 6: of Study protocol of a cluster randomized controlled trial to evaluate effectiveness of a system for maintaining high-quality early essential newborn care in Lao PDR

General Information Questionnaire. (DOCX 20 kb

Additional file 7: of Study protocol of a cluster randomized controlled trial to evaluate effectiveness of a system for maintaining high-quality early essential newborn care in Lao PDR

Informed consent form. (DOCX 23 kb

Additional file 5: of Study protocol of a cluster randomized controlled trial to evaluate effectiveness of a system for maintaining high-quality early essential newborn care in Lao PDR

Checklist of hospital environment facilitating implementation of Early Essential Newborn Care. (DOCX 55 kb