Background and objectives: P53 gene mutation and deletion are among the important molecular markers linked to lung cancer. In most cases, the inactivating mutations affecting both p53 alleles are acquired in somatic cells. Less commonly, the mutations are inherited ones. The aim of the present study was to analyze the frequency of having a wild and/or a mutated p53 gene in lung cancer compared to benign lung lesions and to relate these findings to different morphological types and grades of lung cancer.
Patients, materials and methods: In this retrospective study, the histopathology blocks of 30 lung cancer cases covering the period from2002 to 2007were obtained from the archives of the histopathology sec

Background : the major focus of respiratory cytology is the diagnosis of lung cancer , carcinoma of the lung is now reported to be the most commonly diagnosed non- Cutaneous malignancy in the world. Iraq has faced the increase in incidence of this lethal type of cancer. Sputum cytology is a convenient method of screening and diagnosing primary epithelial tumor of the lung which is of many types include fresh smear ,Sacccomanno smear, and mailing container method.
Methods : Sputum cytological study was done on 50 patients suspected to have pulmonary carcinoma prepared by fresh smear method ,Saccomanno method ,and mailing container
method.One, two,or three samples taken from each patient.Slides were prepared

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

     Radon and its daughters are of the natural radioactive decay of the uranium series. Exposure to radon gas leads to lung cancer, so the risks are significantly higher for smokers than for non-smokers. Therefore, the risk of radon increases for both active and passive smokers. The radioactivity of alpha particles emitted by radium 226, the main source of radon 222, has become harmful because its prevalence and inhalation increase with increased smoking. In this study, a CR-39 detector was used to measure radon, radium, and uranium concentrations and then calculate risk parameters in seven cigarette-smoking females in vitro study of human blood samples, and three normal females with no actual and passive cigarette smoking. The rado

Vitamin K-dependent protein (VKDP) contributes to the development of lung cancer. The purpose of this research was to better understanding of the role of blood matrix Gla protein (MGP), VKDPs, Malondialdehyde (MDA), Superoxide dismutase (SOD) and Vitamin K (Vit K) in Iraqi patients with lung cancer before and after the first cycle of chemotherapy. Blood samples were collected from Al amal National Hospital for cancer treatment from October 2021 to May 2022, and a total of 80 samples were collected, divided into two groups (40 patient before taking a chemotherapy and 40 patients after taking chemotherapy), ranging in age from 20 to 45 years old. The results showed that although there were highly statistically significant differences in MD

Non-Small Cell Lung Cancer (NSCLC) accounts for about 84% of all lung cancer types diagnosed so far. Every year, regardless of gender, the NSCLC targets many communities worldwide. 5-Fluorouracil (5-FU) is a uracil-analog anticancer compound. This drug tends to annihilate multiple tumour cells. But 5-FU's most significant obstacle is that it gets very easily metabolized in the blood, which eventually leads to lower anticancer activity. Therfore a perfect drug delivery system is needed to overcome all the associated challenges.

In this experiment, an attempt was made to prepare 5-FU loaded poly lactic-co-glycolic acid  nanoparticles using solvent evaporation method and subsequently observed the effect of molecular weight of poly l

      Eight-hydroxyguanosine  (8-OHdG) is considered as one of the principle forms of oxygen radicals that stimulated the oxidative stress and has been extensively utilized as a biomarker for oncogenesis. The primary goal of the present study was to investigate the alteration in the levels of 8-OHdG, antioxidant profile and proinflammatory cytokines levels in patients with lung carcinoma. Blood samples were collected from 40 cases with lung cancer (stage III) admitted before the treatment, for health examination at the Nanakaly Hospital in Erbil city and 45 healthy samples of controls with ages ranging between 38-69 years for both groups. Circulating concentration of 8-OHdG, tumor necrosis factor and interleukin-6 were evaluated by

Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.

       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.