There are a few studies that discuss the medical causes for diabetic foot (DF) ulcerations in Iraq, one of them in Wasit province. The aim of our study was to analyze the medical, therapeutic, and patient risk factors for developing DF ulcerations among diabetic patients in Baghdad, Iraq.

Background: Teachers are considered as dynamic force who take a pivotal position in any educational system. Since they may play a significant role in passing the preventive information and health promotion, it is important that their own oral health knowledge, attitude, and practices conform to the professional recommendations. The aim of this study was to evaluate oral health knowledge, attitude and practices among kindergarten teachers, and their impact on teachers’ oral health condition in Al-Rusafa Sector, Baghdad, Iraq. Materials and Methods: This cross-sectional survey was conducted among 80 kindergarten teachers. A self-administered questionnaire was distributed among these teach¬ers. This questionnaire format contains two

YY Lazim, NAB Azizan, 2nd International Conference on Innovation and Entrepreneurship, 2014

Cerium (III), Neodymium (III) and Samarium (III) Complexes existent a wide range of implementation that stretch from their play in the medicinal and pharmaceutical area because of their major significant pharmacological characteristic such as antifungal, anti-cancer, anti-bacterial ,anti-human immunodeficiency virus ,antineoplastic, anti-inflammation,inhibition corrosion,in some industrial (polymers, Azo dye).It is likely to open avenuesto research among various disciplines such as physics, electronics, chemistry and materials science by these complexes that contain exquisitely designed organic molecules.This paper reviews the definition, importance and various applications of Cerium (III), Neodymium (III) and Samarium (III) Complexes anddi

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system