Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

Trigeminal Neuralgia (TN) is one of the most commonly painful cranial neuralgia characterized by paroxysmal attacks as short lasting facial pain along the trigeminal nerve branches. The aim of the present study is to innovate a biochemical relationship between (melatonin, GALNT12 and Zn) and TN and also to examine the biochemical action of tegretol (carbamazepine) as a treatment on the above biochemical parameters. Blood samples were collected from fifty four (54) trigeminal neuralgia patients diagnosed by magnetic radiation image (MRI). Patients were classified into four groups: G3 (40- 70) years composed of (12) diagnosed male (without treatment), G4 (48- 75) years composed of (12) diagnosed female (without treatment), G5 (34- 76)

Background: Endometrial Cancer (EC) is the malignant tumor originating from endometrium cell (lining of the uterus). EC incidence and mortality have increased in recent years. Routinely used methods for EC diagnosis and treatment are histopathological tissue culture after surgery and postoperative radiotherapy, however there is still not enough efficient treatment for recurrence or progression of this disease. So, there is a critical need for further EC identification by new biological ways for the prognostic diagnosis of it. Objective: This study aimed to look for ways by which could help in diagnosis of EC before the hysterectomy. Materials and Methods: 55 patients with EC and 57 healthy women were involved in this study (up to 45 years)

Temporomandibular disorders (TMDs) were investigated in 143 pretreatment orthodontic patients (43 males and 102 females) whose age ranged between 10-25 years at the College of Dentistry, University of Baghdad, Iraq. The study was undertaken to elucidate the prevalence and severity of TMDs in malocclusion patients and to defme the relationships between malocclusion and TMDs. The clinical signs and subjective symptoms were recorded according to the principles introduced by Helkimo (1974b). Subjective symptoms were reported by 65.7% of the patients with 22.40/0 described as severe, and the most common symptoms were TMJ sounds and feeling offatigue. Clinical signs were observed in 81.8% of the sample with 22.4 and 6.3% described as moderate and

KE Sharquie, HA Hassan, AA Noaimi, IRAQI JOURNAL OF COMMUNITY MEDICINE, 2010

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

Human cytomegalovirus (HCMV) infection is ubiquitous and successfully reactivated in patients with immune dysfunction as in patient with multiple myeloma (MM), causing a wide range of life-threatening diseases. Early detection of HCMV and significant advances in MM management has amended patient outcomes and prolonged survival rates.