969 research outputs found
Finalist - Migrant Worker
No full textMigrant Worker by Omer Aziz was one of the five finalists in the 2016 Yale Law Library short story contest
Thoracocentesis
No full textDefinitionThe clinical technique whereby fluid or air is removed from the pleural cavity (see also Chest drain insertion Chapter).IndicationsEmergency: in the acute situation where removal of fluid or air may prevent the restriction of normal ventilation and/or tamponade of the heart.Diagnostic: sampling of fluid in the thoracic cavity for microscopy, culture, serology and cytology. The appearance of the fluid can allude to a diagnosis, for example milky fluid (chyle) aspirated from a ‘chylothorax’ implies rupture of the thoracic duct, while aspiration of blood from a ‘haemothorax’ is usually the result from penetrating chest injuries.Therapeutic: when fluid continually accumulates despite medical therapy, repeated aspiration can provide symptomatic relief.Radiographic: improving radiographs in areas which may otherwise be obscured by radio-opaque fluid in order to further aid diagnosis.ProcedurePre-medication with an intravenous anxiolytic (e.g. midazolam 1.5 mg), which should be given immediately before the procedure, or an intramuscular opioid given one hour before, keeping an antidote at hand.Collect all the correct equipment prior to procedure. The following are recommended: antiseptic preparation solution, sterile gloves, gauze, sterile towels/drapes, 1–2% lidocaine without epinephrine, 3–5 ml syringe and 18-gauge needle (for local anaesthesia), 22-gauge 3.5 cm needle, three-way stopcock, 50 ml syringe, 30 cm long large (16-gauge) catheter-through-needle intravenous placement system, appropriate containers for fluid for diagnostic tests, haemostat, adhesive dressing and an assistant as required.Confirm the site of insertion both clinically and radiologically (unless in emergency when clinical suspicion is enough). Position of the patient depends on whether air or fluid is expected
sj-docx-1-dhj-10.1177_20552076241228408 - Supplemental material for Added value of video edutainment on android handsets in home visits to improve maternal and child health in Bauchi State, Nigeria: Secondary analysis from a cluster randomised controlled trial
No full textSupplemental material, sj-docx-1-dhj-10.1177_20552076241228408 for Added value of video edutainment on android handsets in home visits to improve maternal
and child health in Bauchi State, Nigeria: Secondary analysis from a cluster randomised controlled trial by Umaira Ansari, Khalid Omer, Amar Aziz, Yagana Gidado, Hadiza Mudi, Ibrahim Sabo Jamaare, Neil Andersson and Anne Cockcroft in DIGITAL HEALTH</p
sj-docx-2-dhj-10.1177_20552076241228408 - Supplemental material for Added value of video edutainment on android handsets in home visits to improve maternal and child health in Bauchi State, Nigeria: Secondary analysis from a cluster randomised controlled trial
No full textSupplemental material, sj-docx-2-dhj-10.1177_20552076241228408 for Added value of video edutainment on android handsets in home visits to improve maternal
and child health in Bauchi State, Nigeria: Secondary analysis from a cluster randomised controlled trial by Umaira Ansari, Khalid Omer, Amar Aziz, Yagana Gidado, Hadiza Mudi, Ibrahim Sabo Jamaare, Neil Andersson and Anne Cockcroft in DIGITAL HEALTH</p
<b>Supplemental Material - The Equity Impact of Universal Home Visits to Pregnant Women and Their Spouses in Bauchi State, Nigeria: Secondary Analysis From a Cluster Randomised Controlled Trial</b>
No full textSupplemental Material for The Equity Impact of Universal Home Visits to Pregnant Women and Their Spouses in Bauchi State, Nigeria: Secondary Analysis From a Cluster Randomised Controlled Trial by Anne Cockcroft, Loubna Belaid, Khalid Omer, Umaira Ansari, Amar Aziz, Yagana Gidado, Hadiza Mudi, Rilwanu Mohammed, Rakiya Sale and Neil Andersson in Community Health Equity Research & Policy.</p
An intelligent deep convolutional network based COVID-19 detection from chest X-rays
No full textCoronavirus disease-2019 (COVID-19) seems to be a fast spreading contagious illness that affects both humans and animals. This catastrophic deadly virus has an impact on people's daily lives, their wellbeing, and a nation's economy. According to a clinical research of COVID-19 affected patients, these individuals have been most commonly infected with a lung illness after coming into touch with the virus. A chest X-ray (also known as radiography) or a chest CT scan seems to be more efficient imaging techniques for detecting lung issues. Nonetheless, when compared to a chest CT, a significant chest X-ray remains a less expensive procedure. Thus, in this research, a novel Deep convolution neural network algorithm is presented to detect the COVID-19 from X-ray image. Moreover, to enhance diagnostics sensitivity and reduce error rate, a hybrid Two-step-AS clustering approach with Ensemble Bootstrap aggregating training and Multiple NN methods used. In addition, TSEBANN model has been employed to explore the qualification procedure effects. The proposed algorithm was trained before and after classification while compared to traditional Convolutional Neural Network (CNN). After, the process of pre-processing and feature extraction, the CNN strategy was adopted as an identification approach to categorize the information depending on Chest X-ray recognition. These examples were then classified using the CNN classification technique. The testing was conducted on the COVID-19 X-ray dataset, and the cross-validation approach was used to determine the model’s validity. The result indicated that a CNN system classification has attained an accuracy of 98.062 %
Jérusalem dans l'oeuvre des graveurs israéliens = Jerusalem and the Israeli Printmaker
No full textTracing a history of the Holy City's representation from the sacred texts through Israeli art of the time (1979), Omer briefly presents 18 printmakers through their respective itineraries and styles, stressing their influence on the development and practice of the medium. The author elaborates on Jerusalem's academic institutions, its museums and their collections. Artists alphabetically indexed, with biographical notes and reproductions. Texts in English, French and Hebrew
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