Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

Background: Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease mediated by autoreactive T cells against myelin-basic proteins. Cytokines are suggested to play a role in the etiopathogenesis of the disease. Among these cytokines is interleukin-2 (IL-2). Aim of the study: To investigate the association between IL2+166 G/T single nucleotide polymorphism (SNP: rs2069763) and MS in Iraqi patients. Serum level of IL-2 was also detected. Anti-rubella IgG antibody was further determined in the sera of patients. Patients and methods: Eighty MS patients (28 males and 52 females; age mean ± SD: 39.2 ± 16.1 years) and 80 healthy control matched patients for age (32.15 ± 16.13 years) and gender (28 males and 52 females) were en

    Clopidogrel is a prodrug that must be transformed into an active metabolite by hepatic cytochrome P450 (CYP) isoenzymes to prevent platelet clotting. Polymorphisms of the CYP2C19 gene can cause a reduction or complete loss of CYP2C19 enzyme activity resulting in inhibiting clopidogrel metabolism, effectiveness and increase stroke recurrence risk in ischemic stroke patients. This study aims to investigate the correlation between genetic polymorphisms in CYP2C19*2 and*3 and recurrent risk in patients with ischemic stroke taking clopidogrel 75mg in Kurdistan region –Iraq. This retrospective case-control study was carried out at Kurdistan, Erbil, Medicina medical center, and Rizgary general hospital from January 2021 to

A series of new coumarin and N-amino-2-quinolone derivatives have been synthesized. The reaction of coumarin (1) with excess of  Hydrazine hydrate 98% yielded 1-amino-2-quinolone (2), Compound (2) was reacted with different Sulfonyl chloride to yield Sulfonamides [ N-(2-oxoquinolin-1(2H)-yl) methane sulfonamide (3), N-(2-oxoquinolin-1(2H)-yl) Benzene sulfonamide (4) and 4-methyl-N-(2-oxoquinolin-1(2H)-yl) benzene sulfonamide (5) ], while  reaction of  2-(4-methyl-2-oxo-2H-chromen-7-yloxy) acetic acid (8) with different amines yielded compounds [  2-(4-methyl-2-oxo-2H-chromen-7-yloxy)-N-(2-oxoquinolin-1(2H)-yl) acetamide (9) and N-(5-methyl-1,3,4-thiadiazol-2-yl)-2-(4-methyl-2-oxo-2H-chromen-7-yloxy)acetamide (10) ] th

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

This study was established to investigate the correlation between the expression of matrix metalloproteinases (MMP-1) and the pathogenesis of osteoarthritis (OA). Blood samples were collected from 55 female patients with inflammatory OA and controls for estimation of serum (MMP-1) levels. In the current study, there is significant increase (p<0.001) in the mean of serum MMP-1 levels in osteoarthritis females (4027.73 ± 1345.28 pg/ml) than that in control females (798.76 ± 136.79 pg/ml). It was concluded that MMP-1 may be associated with the pathogenesis of osteoarthritis.