The present study aimed to use the magnetic field and nanotechnology in the field of water purification, which slots offering high efficiency to the possibility of removing biological contaminants such as viruses and bacteria rather than the use of chemical and physical transactions such as chlorine and bromine, and ultraviolet light and boiling and sedimentation and distillation, ozone and others that have a direct negative impact on human safety and the environment. Where they were investigating the presence in water samples under study Coli phages using Single agar layer method and then treated samples positive for phages to three types of magnetic field fixed as follows (North Pole - South Pole - Bipolar) and compare the re

The sunflower plants are attacked by serious seed and soil-borne pathogens including charcoal rot disease that caused by Macrophomina phaseolina. This disease has serious damages to sunflower crop. This study aimed to assess the efficacy of Arbuscular mycorrhizal fungus against charcoal rot disease as fungicide alternative.

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

              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

In this paper an eco-epidemiological system has been proposed and studied analytically as well as numerically. The boundedness, existence and uniqueness of the solution are discussed. The local and global stability of all possible equilibrium point are investigated. The global dynamics is studied numerically. It is obtained that system has rich in dynamics including Hopf bifurcation.

Diabetic retinopathy (DR) is a diabetes- caused disease that is associated with  leakage of fluid from the blood vessels into the retina, leading to its damage. It is one of the most common diseases that can lead to weak vision and even blindness. Exudates is a clear indication of diabetic retinopathy, which is the main cause of blindness in people with diabetes. Therefore, early detection of exudates is a crucial and essential step to prevent blindness and vision loss is in the analysis of digital diabetic retinopathy systems. This paper presents an improved approach for detection of exudates in retina image using supervised-unsupervised Minimum Distance (MD) segmentation method. The suggested system includes three stages; First, a

     Heart disease is a non-communicable disease and the number 1 cause of death in Indonesia. According to WHO predictions, heart disease will cause 11 million deaths in 2020. Bad lifestyle and unhealthy consumption patterns of modern society are the causes of this disease experienced by many people. Lack of knowledge about heart conditions and the potential dangers cause heart disease attacks before any preventive measures are taken. This study aims to produce a system for Predicting Heart Disease, which benefits to prevent and reduce the number of deaths caused by heart disease. The use of technology in the health sector has been widely practiced in various places and one of the advanced technologies is machine lea

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