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Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>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 based on the fusion of probabilities. Individually, the classifier based on PI achieved 93.1% accuracy, whereas the deep classifiers reached classification accuracies over 90% only in isolated cases. Overall, the average accuracy of the deep networks over the four corneal maps ranged from 86% (SfN) to 89.9% (AN). The classifier ensemble increased the accuracy of the deep classifiers based on corneal maps to values ranging (92.2% to 93.1%) for SqN and (93.1% to 94.8%) for AN. Including in the ensemble-specific combinations of corneal maps’ classifiers and PI increased the accuracy to 98.3%. Moreover, visualization of first learner filters in the networks and Grad-CAMs confirmed that the networks had learned relevant clinical features. This study shows the potential of creating ensembles of deep classifiers fine-tuned with a transfer learning strategy as it resulted in an improved accuracy while showing learnable filters and Grad-CAMs that agree with clinical knowledge. This is a step further towards the potential clinical deployment of an improved computer-assisted diagnosis system for KCN detection to help ophthalmologists to confirm the clinical decision and to perform fast and accurate KCN treatment.</p>
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Publication Date
Sat Jan 01 2022
Journal Name
Tropical Journal Of Natural Product Research
Detection of Herpes Simplex Virus Type 1 in Patients Affected by Conjunctivitis
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Herpes simplex virus (HSV) is a common human pathogen that causes severe infections in newborns and immunocompromised patients. Conjunctivitis or corneal epithelial keratitis is caused by HSV type 1 all over the world and at all times of the year. The present study was aimed at detecting HSV in patients suffering from conjunctivitis. One hundred and ten (110) clinical samples (90 patients and 20 controls, both males and females) of eye conjunctiva swabs were collected from patients of different ages. The samples were analyzed using qPCR and ELISA techniques. The qPCR results revealed that HSV was present in 47 (52.2%) of the 90 patients who were infected. Of these patients, 25 (48.0%) were males and 22 (57.8%) were females, indicati

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Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography 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.

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Global Pharma Technology
Detection of HBME-1 and galectin-3 by immunohistochemistry in follicular lesions
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The main problem established by a discovery of a thyroid nodule is to discriminate between a benign and malignant lesion. Differential diagnosis between follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. A developing number of some encouraging IHC markers for the differential diagnosis of thyroid lesions have emerged, including, Hector Battifora mesothelial (HBME-1) and galectin-3 (Gal-3). There was significant positive correlation between Galectin-3 and HBME-1 in follicular carcinoma and follicular variant of papillary carcinoma (r= 0.380, P= 0.041) and (r= 0.315, P=0.047) respectively. There was no significant correlation between

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Scopus
Publication Date
Mon Dec 28 2020
Journal Name
The Iraqi Journal Of Veterinary Medicine
Serological and Molecular Phylogenetic Detection of Coxiella burnetii in Lactating Cows, Iraq
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This study is carried out to investigate the prevalence of Coxiella burnetii (C. burnetii) infections in cattle using an enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) assay targeting IS1111A transposase gene. A total of 130 lactating cows were randomly selected from different areas in Wasit province, Iraq and subjected to blood and milk sampling during the period extended between November 2018 and May 2019. ELISA and PCR tests revealed that 16.15% and 10% of the animals studied were respectively positive. Significant correlations (P<0.05) were detected between the positive results and clinical data. Two positive PCR products were analyzed phylogenetically, named as C. burnetii IQ-No.5 and C. burnet

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Publication Date
Fri Mar 19 2021
Journal Name
Annals Of The Romanian Society For Cell Biology
Molecular Detection of Acientobacter Baumannii Isolated From Nosocomial Infections in Baghdad Hospitals
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&nbsp;The present study is an attempt for detection of A. baumannii by conventional and PCR methods using species-specific primers for these A. baumannii. A total of 87 samples were collected from hospitals in Baghdad (Al-Rasafa and Al-Karkh Hospitals) during the period from 2019 to 2020.The samples included: 40 specimens, from wounds, respiratory infections (sputum), burns, CSF and 47 samples from the hospital environment (swabs), while samples collected from intensive care unit including patient beds, surgical instruments and appliances, emergency lobby and baby incubators. A. baumannii isolate identification depending on the morphologic characteristics on the culture media including, blood agar, MacConkey&nbsp; agar, as well as t

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Detection of blaKPC Gene in Some Clinical Klebsiella pneumoniae Isolates in Baghdad
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For the period from February 2014 till May 2014, one hundred and nine lactose fermenter clinical isolates from different samples (urine, stool, wound swab, blood, and sputum) were collected from Alyarmok, Alkadimiya, and Baghdad teaching hospitals at Baghdad governorate. Identification of all Klebsiella pneumoniae isolates were carried out depending on macroscopic, microscopic characterizations, conventional biochemical tests, and Api 20E system. Fifty-three (48.62%) isolates represented K. pneumoniae; however, 51.73% represented other bacteria. Susceptibility test was achieved to all fifty-three K. pneumoniae isolates using five antibiotic disks (Ceftazidime, Ceftriaxone, Cefotaxime, Imipenem, and Meropenem). Most of tested isolates (90

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Publication Date
Fri Mar 04 2022
Journal Name
Pakistan Journal Of Medical And Health Science
Detection of aadA1 and aac(3)-1V resistance genes in Acinetobacter baumannii
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Publication Date
Tue Apr 01 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
The Impact of Feature Importance on Spoofing Attack Detection in IoT Environment
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The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

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Publication Date
Tue Apr 01 2025
Journal Name
Iop Conference Series: Earth And Environmental Science
Molecular Detection and Antiserum Preparation of Begomoviruses Infecting Zucchini Squash in Iraq
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Abstract<p>Begomoviruses infecting zucchini squash were investigated. Leaf samples were collected from zucchini squash growing areas in Baghdad (Jhadryaa and Yusufiyah), Babylon (Jibela and Mahmudiyah) and Diyala (Khan Bani Saad) Provinces. Samples were screened for the presence of begomoviruses using polymerase chain reaction (PCR) and Deng genus specific primers. Sixteen out of 40 samples were begomovirus positive. Sequence analysis confirmed the detection of Tomato leaf curl Palampur virus (TLCPALV) <italic>Begomovirus solanumpalampurense</italic>, Squash leaf curl virus (SLCuV) <italic>B. cucurbitapeponis</italic> and Tomato yellow leaf curl virus (TYLCV) <italic>B. </italic></p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
مجلة الأطروحة العلمية المحكمة-العلوم الصرفة والتطبيقية
Detection of Lead (Pb) and Cadmium (Cd) Concentrations in Some Indomie Samples
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