Autoencoderbased recognition involving nearsurface flaws inside ultrasound tests

DMF index was very low in 2 articles and low-to-high in 3 articles.
Low dental caries susceptibility with AI patients was noticed in this study. A possible factor could be the lack of proximal contacts and elimination of fissures through enamel loss. The lack of dental caries susceptibility was also explained by the microbacterial specificity of hypoplastic AI patients. Moreover, it was also noted that the prevalence of dental caries among AI patients depends on sociodemographic change.
Low dental caries susceptibility with AI patients was noticed in this study. A possible factor could be the lack of proximal contacts and elimination of fissures through enamel loss. The lack of dental caries susceptibility was also explained by the microbacterial specificity of hypoplastic AI patients. Moreover, it was also noted that the prevalence of dental caries among AI patients depends on sociodemographic change.
The level of evidence (LOE) of Saudi dental research from 2000 to 2020 was evaluated, and factors associated with the LOE were determined.
This study was a systematic review. PubMed, Web of Science, and Medline databases were utilized to retrieve available dental articles published in English between January 2000 and May 2020. The inclusion criteria consisted of clinical studies conducted in Saudi Arabia with at least one Saudi dental affiliation. The retrieved eligible articles were evaluated independently by two reviewers using a modified Oxford LOE scale. The LOE of the studies was compared between the last two decades.
Of the 7237 articles identified, 1557 articles met the inclusion criteria. Approximately 78% of the published articles reported Level IV evidence. A higher trend toward Level I, II, and III publications has occurred in recent years (i.e., 2010-2020). However, no statistically significant difference existed in LOE proportions between the two decades. The presence of international collaboration and high journals' impact factor was significantly associated with a higher LOE.
Most published dental research studies were low LOE studies (i.e., Level IV). National and international collaboration is highly encouraged as this is a factor, according to our findings, that would be a positive addition toward publishing dental research of a higher LOE in Saudi Arabia.
Most published dental research studies were low LOE studies (i.e., Level IV). National and international collaboration is highly encouraged as this is a factor, according to our findings, that would be a positive addition toward publishing dental research of a higher LOE in Saudi Arabia.
Prostate biopsy remains an important surgical procedure in the diagnostic pathway for prostate cancer, but access to prostate biopsy service is poorly studied in the Nigerian population. While there has been a well-documented delay in patient presentation with prostate cancer in Nigeria, little is however known about how long patients wait to have a histological diagnosis of prostate cancer and start treatment after presenting at Nigerian hospitals.
This was a descriptive retrospective study to document the specific duration of the various timelines in getting a diagnosis of prostate cancer at the Lagos State University Teaching Hospital, Ikeja, Nigeria.
There were 270 patients. DPCPX purchase The mean age was 69.50 ± 8.03 years (range 45-90). The mean PSA at presentation was 563.2 ± 1879.2 ng/ml (range 2.05-15400), and the median PSA was 49.3 ng/ml. The median waiting times were (i) 10 days from referral to presentation; (ii) 30 days from presentation to biopsy; (iii) 24 days from biopsy to review of histology; (iv) the waiting time from patient presentation to having a biopsy done and the histology report waiting time.
Gallbladder cancer (GBC), which accounts for more than 80% of biliary tract malignancies, has a poor prognosis with an overall 5-year survival less than 10%. The study aimed to identify risk factors and develop a predictive model for GBC following surgical resection.
98 GBC patients who underwent surgical resection from Guangdong Provincial People's Hospital were enrolled in the study. Cox-regression analysis was performed to identify significant prognostic factors. A nomogram was constructed and Harrell's concordance index, calibration plot, and decision cure analysis were used to evaluate the discrimination and calibration of the nomogram.
Liver resection, tumor size, perineural invasion, surgical margin, and liver invasion were identified as independent risk factors for overall survival (OS) in GBC patients who underwent surgical resection. Based on the selected risk factors, a novel nomogram was constructed. The C-index of the nomogram was 0.777, which was higher than the American Joint Committee on Cancer (AJCC) staging system (0.724) and Nevin staging system (0.659). Decision cure analysis revealed that the nomogram had a better net benefit and the calibration curves for the 1-, 3-, and 5-year survival probabilities were also well matched with the actual survival rates. Lastly, high-risk GBC were stratified based on the scores of the nomogram and we found high-risk GBC were associated with both worse OS and disease-free survival (DFS).
We developed a nomogram showing a better predictive capacity for patients' survival of resected GBC than the AJCC staging systems. The established model may help to stratify high-risk GBC and facilitate decision-making in the clinic.
We developed a nomogram showing a better predictive capacity for patients' survival of resected GBC than the AJCC staging systems. The established model may help to stratify high-risk GBC and facilitate decision-making in the clinic.This paper introduced a relatively new mixture distribution that results from a mixture of Fréchet-Weibull and Pareto distributions. Some properties of the new statistical model were derived, such as moments with their related measures, moment generating function, mean residual life function, and mean deviation. Furthermore , different estimation methods were introduced for determining the unknown parameters of the proposed model. Finally, we introduced three real data sets which were applied to our distribution and compared them with other well-known statistical competitive models to show the superiority of our model for fitting the three real data sets, and we can clearly see that our distribution outperforms its competitors. Also, to verify our results, we carried out the existence and uniqueness test to the log-likelihood to determine whether the roots are global maximum or not.The new coronavirus, COVID-19, has affected people all over the world. Coronaviruses are a large group of viruses that can infect animals and humans and cause respiratory distress; these discomforts may be as mild as a cold or as severe as pneumonia. Correct detection of this disease can help to avoid its spreading increasingly. In this paper, a new CAD-based approach is suggested for the optimal diagnosis of this disease from chest X-ray images. The proposed method starts with a min-max normalization to scale all data into a normal scale, and then, histogram equalization is performed to improve the quality of the image before main processing. Afterward, 18 different features are extracted from the image. To decrease the method difficulty, the minimum features are selected based on a metaheuristic called Archimedes optimization algorithm (AOA). The model is then implemented on three datasets, and its results are compared with four other state-of-the-art methods. The final results indicated that the proposed method with 86% accuracy and 96% precision has the highest balance between accuracy and reliability with the compared methods as a diagnostic system for COVID-19.Gesture recognition is one of the important ways of human-computer interaction, which is mainly detected by visual technology. The temporal and spatial features are extracted by convolution of the video containing gesture. However, compared with the convolution calculation of a single image, multiframe image of dynamic gestures has more computation, more complex feature extraction, and more network parameters, which affects the recognition efficiency and real-time performance of the model. To solve above problems, a dynamic gesture recognition model based on CBAM-C3D is proposed. Key frame extraction technology, multimodal joint training, and network optimization with BN layer are used for making the network performance better. The experiments show that the recognition accuracy of the proposed 3D convolutional neural network combined with attention mechanism reaches 72.4% on EgoGesture dataset, which is improved greatly compared with the current main dynamic gesture recognition methods, and the effectiveness of the proposed algorithm is verified.Lung cancer is the uncontrolled growth of cells in the lung that are made up of two spongy organs located in the chest. These cells may penetrate outside the lungs in a process called metastasis and spread to tissues and organs in the body. In this paper, using image processing, deep learning, and metaheuristic, an optimal methodology is proposed for early detection of this cancer. Here, we design a new convolutional neural network for this purpose. Marine predators algorithm is also used for optimal arrangement and better network accuracy. The method finally applied to RIDER dataset, and the results are compared with some pretrained deep networks, including CNN ResNet-18, GoogLeNet, AlexNet, and VGG-19. Final results showed higher results of the proposed method toward the compared techniques. The results showed that the proposed MPA-based method with 93.4% accuracy, 98.4% sensitivity, and 97.1% specificity provides the highest efficiency with the least error (1.6) toward the other state of the art methods.
In high TB/HIV settings, the increased risk for TB amongst children exposed to HIV has been established through biomedical tests. Screening HIV exposed children for TB can improve early childhood TB detection and treatment.
This study assessed the utility of a modified World Health Organization (WHO) tool by including HIV variables, to determine TB exposure amongst HIV exposed children presenting to a "Well Child" Clinic (CWC).
Clinical data were obtained from medical records and/or from the caregivers of children presenting to CWC. Data was analyzed to explore factors associated with positive screening for TB, including being exposed to HIV and current HIV status.
Five percent (55/1100) screened reported a close TB contact and 21% (n=231) had positive TB symptom screen. History of close TB contact was a risk factor for positive screening for TB symptoms (OR 1.89 CI 1.05-3.4) while being HIV negative was protective (OR 0.3, Cl 0.19-0.62). HIV exposure was associated with increased risk of TB exposure (OR 2.9 CI 1.61-5.19).
Integrating HIV variables in the existing WHO screening tool for childhood TB can be useful in early detection and treatment of TB in HIV exposed children in resource limited settings.
Integrating HIV variables in the existing WHO screening tool for childhood TB can be useful in early detection and treatment of TB in HIV exposed children in resource limited settings.