The study aims at investigating the quality of internal auditing and its impact on nature, timing, and procedures of external audit, based on international auditing standards, in particular ISA (610). The standard ISA (610) requires the external auditors to assess independence, the scope of internal audit unit, competence, and due professional care of internal auditors as indicators that reflect the quality of internal audit performance before deciding to rely on internal auditors.

The sample of this study consisted of external auditors in Iraqi Solidary Companies for Auditing. A questionnaire was distributed to them via e-mail

BACKGROUND: Hospital training courses for pharmacy students were required to prepare students to meet the challenges of real-world hospital work. AIM: Because there have been few studies on the efficacy of such courses, we aimed to recognize recent graduates’ perceptions, benefits, and factors influencing the quality of hospital training courses for pharmacy students. METHODS: A qualitative study using a phenomenology approach was conducted in 2022 and included several hospitals in Baghdad, Iraq, using in-depth face-to-face individual-based semi-structured interviews. Until saturation, a convenient sample of recently graduated pharmacists was included. The obtained data were analyzed using a thematic content analysis approach

Been investigating a Pfyrus antigen hepatitis pattern J and Virus-positive rubella viral hepatitis antibodies pattern J. declaration followed by the percentage rate-positive patients of measles Allmana antibodies

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c