Background: Poly cystic ovary syndrome is a common disorder in women of reproductive age, it is associated with disturbance of reproductive, endocrine and metabolic functions. The pathophysiology of PCOS appears to be multifactorial and polygenic. Leptin seems to play an important role in pathophysiology of PCOS especially in women with BMI ≥25kg/m2. Objectives: To assess leptin level in both PCOS and healthy women and explore the relation to their body weight and body mass index. Patient and Methods: A total of 120 women were enrolled in this study, 60 women (50%) had PCOS (study group) and the reminder 60 women (50%) were healthy women and considered as control group. BMI was calculated first. Both groups were further sub

Background. Echinococcosis/ hydatitdosis is a zoonotic parasitic disease caused by the infestation of the larval form of the tapeworm of the genus Echinococcus .The Liver, lungs, and kidneys are the common areas of infestation.Objectives: To describe hydatid disease in hospitalized patients from a clinico-epidemiological perspectives.Methods:: A retrospective study was conducted over a period of 6 months extending from 15th of November 2011 to the 15th of May 2012 by reviewing records of 125 patients who were hospitalized at Baghdad Teaching Hospital during 2011and received medical and surgical treatment for hydatid cyst disease. The information covered the socio-demographic and clinical characteristics of the patientsResults:.The presen

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

In this paper, a mathematical model consisting of a prey-predator system incorporating infectious disease in the prey has been proposed and analyzed. It is assumed that the predator preys upon the nonrefugees prey only according to the modified Holling type-II functional response. There is a harvesting process from the predator. The existence and uniqueness of the solution in addition to their bounded are discussed. The stability analysis of the model around all possible equilibrium points is investigated. The persistence conditions of the system are established. Local bifurcation analysis in view of the Sotomayor theorem is carried out. Numerical simulation has been applied to investigate the global dynamics and specify the effect

              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

A superb demonstration of one of the wonders of technology providing the people with great aid is the employment of Artificial Intelligence in the medical field, and mainly the introduction of Clinical Decision Support Systems (CDSS). Nevertheless, non-’black-box’ AI systems have a significant problem, that is, although they are visible and understandable, there is still a considerable issue of trust by healthcare professionals. Explainable AI (XAI) technology is a means to overcome all the obstacles by unveiling more and offering the explanations of the procedures that AI performs in decision making. This study was conducted by examining various widely used approaches to XAI, which illustrate how XAI verifies the trustworthiness of CDS

Background: Gastroesophageal reflux disease, is a quite prevalent gastrointestinal disease, among which gastric content (excluding the air) returns into the oral cavity. Many 0ral manifestations related t0 this disease include tooth wear, dental caries also changes in salivary flow rate and pH. This study was conducted among gastroesophageal reflux disease patients in order to assess tooth wear in relation to salivary flow rate and pH among these patients and the effect of gastroesophageal reflux disease duration on this relation. Materials and methods: One hundred patients participate in this cross-sectional study for both genders and having an age range of 20-40 years old, patients had been endoscopically identified as having gastroeso

Objectives: This study aimed to identify and analyse ATP7B variants in Iraqi adults with Wilson disease (WD) by long-read next-generation sequencing. Methods: This cross-sectional study was conducted at the Poisoning Consultation Center at Ghazy Al-Hariri Hospital for Surgical Specialties and the Gastroenterology Consultation Clinic at Baghdad Teaching Hospital, Medical City in Baghdad, Iraq. Unrelated patients with clinical and biochemical features suggestive of WD were recruited between October 2022 and October 2023. DNA was extracted from peripheral blood samples. Variants in the ATP7B gene were identified using long-read next-generation sequencing and then analysed by in-silico tools. Results: A total of 45 patients were recruited in