Background: The figure for the clinical application of computed tomography have been increased significantly in oral and maxillofacial field that supply the dentists with sufficient data enables them to play a main role in screening osteoporosis, therefore Hounsfield units of mandibular computed tomography view used as a main indicator to predict general skeleton osteoporosis and fracture risk factor. Material and Methods: Thirty subjects (7 males &23 females) with a mean age of (60.1) years underwent computed tomographic scanning for different diagnostic assessment in head and neck region. The mandibular bone quality of them were determined through Hounsfield units of CT scan images and were correlated with the bone mineral density values obtained from t-scores of lumbar spine using dual x-ray absorptiometry scans (DEXA). Results: There was a highly signifi¬cant positive correlation [p-value 0.000 (HS)] of bone mineral density that measured by t-score of dual x-ray absorptiometrical scan and Hounsfield units with very strong relation in measuring the bone density (r test) = 0.969, this close relation lead to predict osteoporosity and the chance of fracture occurrence using a statistical equation that classified the patients as osteoporotic. Conclusion: Hounsfield units obtained from computed tomography scans that are made for any purposes can provide an alternative clinical parameter to predict osteoporosis at no additional cost to the patient and no additional radiation.
Lymphoma is a cancer arising from B or T lymphocytes that are central immune system components. It is one of the three most common cancers encountered in the canine; lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic conditions and to improve decision-making around treating and what treatment type to use. This study aimed to evaluate a potential novel biomarker related to iron metabolism,
... Show MoreEchocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.
Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show MoreDetection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
... Show MoreIn order to investigate the presence of methicillin or multidrug resistant Staphylococcus aureus in food-chain especially Cows raw milk and white raw soft cheese and its whey, a total of 30 samples were collected randomly from different markets in Baghdad Province during December 2012 till February 2013, in which samples were analyzed by a standard isolation protocols of food microbiology with some modification processing by new, modern and rapid technology tools such as chromogenic medium Baird-Parker agar, Electronic RapIDTM Staph Plus Code Compendium Panel System (ERIC®) Dryspot Staphytect Plus and Penicillin Binding Protein (PBP2') Plus assays; as well as, studying the susceptibility of isolates to different selected antibiotics. The r
... Show MoreEstablishing the systemic character of vocabulary, its relationship with other language systems, their interdependence creates the possibility of a comprehensive scientific study and description of the lexical system of each language, as well as contrastive comparative studies of several languages, including their phraseological composition.
It is known that not all words-components of phraseological units are equivalent in their role in the formation of the semantic content of phraseological units. In this regard, it is necessary to introduce the concept of a lexical dominant. To this we include words, which are kind of centers around which the entire semantic complex of phraseological units, the entire set of its words-componen
... Show MoreBioremoval of chromium from wastewater of tannery factory in Iraq was studied. The bacteria Proteus vulgaris 7E showed an enhanced capability in biosorping chromium when its concentration increased in the solution, reaching a maximum of 476,7 mg/ ml out of 492 mg/ ml under optimum conditions at pH 6 and 50°C at one hour contact time and biomass of 1 mg/ml. The present results showed that dead cells of P. vulgaris 7E biosorbed 87.41 mg/ml of chromium in comparison with91.18 mg/ml of chromium biosorbed by living cells, this indicates the insignificant effect of physiological state of cells. It was found that the above biosorption is physico-chemical process depends upon electrostatic attraction forces. The results has illustrated that the
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