Enhanced Artificial Intelligence System for Diagnosing and Predicting Breast Cancer Using Deep Learning

Breast cancer is the leading cause of death among women with cancer. Computer-aided diagnosis is an efficient method for assisting medical experts in early diagnosis, improving the chance of recovery. Employing artificial intelligence (AI) in the medical area is very crucial due to the sensitivity of this field. This means that the low accuracy of the classification methods used for cancer detection is a critical issue. This problem is accentuated when it comes to blurry mammogram images. In this paper, convolutional neural networks (CNNs) are employed to present the traditional convolutional neural network (TCNN) and supported convolutional neural network (SCNN) approaches. The TCNN and SCNN approaches contribute by overcoming the shift and scaling problems included in blurry mammogram images. In addition, the flipped rotation-based approach (FRbA) is proposed to enhance the accuracy of the prediction process (classification of the type of cancerous mass) by taking into account the different directions of the cancerous mass to extract effective features to form the map of the tumour. The proposed approaches are implemented on the MIAS medical dataset using 200 mammogram breast images. Compared to similar approaches based on KNN and RF, the proposed approaches show better performance in terms of accuracy, sensitivity, spasticity, precision, recall, time of performance, and quality of image metrics

mawdoo3 ai at madar shared task arabic fine grained dialect identification with ensemble learning

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Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

The Effect of Short Term Resting Periods on Maintaining Vertical Jump Accuracy in Swinging the Arms and Without Swinging Them – Comparativ Study

This study aimed to identify the effect of short term resting periods (30, 90, and 120 seconds) on maintaining vertical jump accuracy in two settings: swinging the arms and without swinging them. A secondary aim of the study was to investigate whether swinging the arms would affect vertical jump accuracy. Vertical jump accuracy was examined by asking (120) students from PE faculties at University of Jordan, who were selected intentionally, to jump at the level (67%) of their maximal vertical jump capacity. For the purposes of statistical analyzing, using SPSS, each of means, standard deviations, ANOVA, and t-test were calculated. Results showed no significant differences between three short time resting periods (30, 90, and 120 seconds) on vertical jump accuracy regardless arms swinging (p ≥ .05). Moreover, swinging arms did not influence vertical jump accuracy after any of the three short time resting periods (p ≥ .05). A necessity of using deep mental and perceptual processes in skills\u27 learning has been recommended as it helps in better storing of movement information and subseqeutnly speeds the larning process

Compact UWB 1:2:1 unequal-split 3-way bagley power divider using non-uniform transmission lines

In this paper, compact Ultra-Wide Band (UWB) 1:2:1 unequal split modified Bagley Power Divider (BPD) using Non-Uniform Transmission Lines (NTLs) theory is designed and tested. Based on this theory, 42.44% and 31.1% size reductions are obtained in the lower and upper λ/4 Uniform Transmission Lines (UTLs) in the first and second sections of the proposed divider. To evaluate the effect of the divider’s compactness on its performance, it is compared with UWB 1:2:1 unequal split BPD using Tapered Transmission Lines (TTLs). Both dividers show good results where the measured return loss is appeared to be S11 < −10.6 dB and < −13.4 dB for NTL and TTL BPDs, respectively. However, the insertion losses S12 = S14 and S13 are around −6 ± 1.5 dB and–3 ± 1.3 dB, respectively for both dividers. In this study, simulations are carried out using High-Frequency Structure Simulator (HFSS) software. The evaluation of the proposed divider is obtained from the simulation and hardware measurements results