Deep learning-enabled detection of hypoxic–ischemic encephalopathy after cardiac arrest in CT scans: a comparative study of 2D and 3D approaches

ObjectiveTo establish a deep learning model for the detection of hypoxic–ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format.Methods168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.6%) without signs of HIE. These images were randomly divided into a training and a test set, and five deep learning models based on based on Densely Connected Convolutional Networks (DenseNet121) were trained and validated using different image input formats (2D and 3D images).ResultsAll optimized stacked 2D and 3D networks could detect signs of HIE. The networks based on the data as 2D image data stacks provided the best results (S100: AUC: 94%, ACC: 79%, S50: AUC: 93%, ACC: 79%). We provide visual explainability data for the decision making of our AI model using Gradient-weighted Class Activation Mapping.ConclusionOur proof-of-concept deep learning model can accurately identify signs of HIE on CT images. Comparing different 2D- and 3D-based approaches, most promising results were achieved by 2D image stack models. After further clinical validation, a deep learning model of HIE detection based on CT images could be implemented in clinical routine and thus aid clinicians in characterizing imaging data and predicting outcome

TACRM: trust access control and resource management mechanism in fog computing

https://hcis-journal.springeropen.com/articles/10.1186/s13673-019-0188-3#Abs1Fog computing network is designed as an extension of the cloud due to the need for a supporting platform capable of ensuring the requirements of Internet of Thing (IoT). The growth of fog based fifth generation mobile communication (5G) system is challenged by the need for data sharing security. In fact, without properly securing access to Fog node resources in IoT network, services providers may not be able to achieve the desired performance. Indeed, fog computing obviously confront numerous security and privacy risks, due to its features, such as huge scale geolocation, heterogeneity and mobility. Thus, we propose a security model that is based on cooperation between IoT and fog. This model integrates an efficient access control process associated with a monitoring scheme to ensure secure cooperation between diverse resources and different operational parts. Indeed, a comprehensive scheduling process and resource allocation mechanism using our security model is proposed to improve the intended performance of the system. In fact, our main contribution is to introduce a distributed access control based on security resource management framework for fog-IoT networks, and proactive security scheme under ultra-trustworthiness and low-latency constraints. After evaluation based on iFogSim, we have proved that our scheme not only provides low latency with high security and privacy, but also reduces the complexity of administration and management of security and resources mechanisms

The impact of clothing style on bone mineral density among post menopausal women in Morocco: a case-control study

BACKGROUND: The clothing style is an important factor that influences vitamin D production and thus bone mineral density. We performed a case-control study in order to evaluate the effect of veil wearing (concealing clothing) on bone mineral density in Moroccan post menopausal women. METHODS: The cases were osteoporotic women whose disease was assessed by bone mineral density measurement. Each patient was matched with a non osteoporotic woman for age, and body mass index. All our patients were without secondary causes or medications that might affect bone density. The veil was defined as a concealing clothing which covered most of the body including the arms, the legs and the head. This definition is this of the usual Moroccan traditional clothing style. RESULTS: 178 post menopausal osteoporotic patients and 178 controls were studied. The mean age of the cases and the controls was 63.2 years (SD 7) and the mean body mass index was 32.1 (SD 8). The results of crude Odds Ratios analyses indicated that wearing a veil was associated with a high risk of osteoporosis: OR 2.29 (95% CI, 1.38–3.82). Multiparity or a history of familial peripheral osteoporotic fractures had also a significant effect on increasing the osteoporosis risk (ORs: 1.87 (95% CI, 1.05–3.49) and 2.01 (95% CI, 1.20–3.38)). After a multiple regression analysis, wearing the veil and a history of familial osteoporotic fractures remained the both independent factors that increased the osteoporosis risk (ORs: 2.20 (95% CI, 1.22–3.9) and 2.19 (95% CI, 1.12–4.29) respectively). CONCLUSION: our study suggested that in Moroccan post menopausal women, wearing a traditional concealing clothing covering arms, legs and head increased the risk of osteoporosis. Further studies are required to evaluate the clinical impact of the above findings and to clarify the status of vitamin D among veiled women in Morocco

Toward standardization of BK virus monitoring: evaluation of the BK virus R-gene kit for quantification of BK viral load in urine, whole-blood, and plasma specimens.

Screening of BK virus (BKV) replication is recommended to identify patients at increased risk of BKV-associated diseases. However, the heterogeneity of molecular techniques hinders the establishment of universal guidelines for BKV monitoring. Here we aimed to compare the performance of the CE-marked BK virus R-gene kit (R-gene) to the performance of our in-house assay for quantification of BKV DNA loads (BKVL). A 12-specimen panel from the Quality Control for Molecular Diagnostics (QCMD) organization, 163 urine samples, and 88 paired specimens of plasma and whole blood (WB) from transplant recipients were tested. Both the R-gene and in-house assays showed a good correlation within the QCMD panel (r = 0.995 and r = 0.989, respectively). BKVL were highly correlated between assays, although positive biases were observed with the in-house assay in analysis of urine (0.72 ± 0.83 log10 copies/ml), plasma (1.17 ± 0.63 log10 copies/ml), and WB (1.28 ± 0.37 log10 copies/ml). Recalibration with a common calibrator significantly reduced the bias in comparisons between assays. In contrast, BKVL was underestimated with the in-house PCR in eight samples containing BKV genotype II, presenting point mutations at primer-annealing sites. Using the R-gene assay, plasma and WB specimens were found to be equally suitable for quantification of BKVL, as indicated by the high correlation coefficient (r = 0.965, P < 0.0001). In conclusion, the R-gene assay demonstrated reliable performance and higher accuracy than the in-house assay for quantification of BKVL in urine and blood specimens. Screening of BKV replication by a well-validated commercial kit may enable clinical laboratories to assess viral loads with greater reproducibility and precision.comparative studyevaluation studiesjournal articleresearch support, non-u.s. gov't2014 Dec2014 10 08importe