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

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

Colorectal cancer (CRC) is the most common gastrointestinal malignancy and one of the top ten common cancers worldwide with approximately 2 million cases. There are multiple risk factors that could lead to CRC emergence; of which are genetic polymorphisms. Excision repair cross-complementing group 2 (ERCC2) gene encodes for ERCC2 enzyme which plays a crucial role in maintaining genomic integrity by removing DNA adducts. Several studies suggested that there could be a link between genetic polymorphisms of ERCC2 gene and the risk of CRC development. Hence the present study aims to validate the relationship between the following ERCC2 single nucleotide polymorphisms (rs13181, rs149943175, rs530662943, and rs1799790) and CRC susceptibility. A t

This study examines the factors that affect oral participation of six Arab postgraduate students (two Iraqis, two Jordanians, and two Libyans), namely, three male participants and three female participants. For this purpose, a semi-structured interview was employed. The results showed that female as well male interviewees share some factors that make oral participation in classroom disheartening. These factors include high levels of anxiety, lack of confidence, shyness, and lack of preparation. It was also that there is no difference between male and female interviewees in relation to the factors that make them feel disheartened from oral classroom participation.

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

     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

Background: Non-small cell lung cancer (NSCLC) is caused of 85% of all lung cancers. Among the most important factors for lung tumor growth and proliferation are the tyrosine kinase receptors that coded by the epidermal growth factor recep-tor (EGFR) gene. Activation of EGFR ultimately leads to developing of lung cancer. The present study was undertaken with an objective to detect EGFR mutations in bronchial wash from Iraqi patients with NSCLC before treatment. Methods: DNA was extracted from bronchial wash samples collected from 50 patients with NSCLC by using a Qiamp DNA Mini Kit (Qiagen, Hilden, Germany). Then, EGFR mutations were determined by using real-time RCR combined with two technologies, Amplification Refractory Mutation System (