<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

Objective: Using green chemistry, an effective, inexpensive, and environmentally safe method, sulfur nanoparticles with specific properties can be prepared and used in nanotechnology. This research aimed to prepare sulfur nanoparticles from chilli pepper extract and determine their effectiveness against colon cancer. Method: Chilli pepper extract obtained from local markets was treated with aqueous sodium thiosulfate (Na2S2O7.5H2O). After mixing, it was continuously stirred, heated, and filtered. NaBH4 was then added, resulting in a yellow precipitate. The precipitate was centrifuged, purified, and dried at 250°C. Results: Standardised tests such as UV-Vis, XRD, SEM, TEM, AFM, and EDX were used, resulting in sulfur nanoparticles with an av

Background: Breast cancer is the most common cancer in Iraq and the United Kingdom. While the disease is frequently diagnosed among middleaged Iraqi women at advanced stages accounting for the second cause of cancer-related deaths, breast cancer often affects elderly British women yielding the highest survival of all registered malignancies in the UK. Objective: To compare the clinical and pathological profiles of breast cancer among Iraqi and British women; correlating age at diagnosis with the tumor characteristics, receptor-defined biomarkers and phenotype patterns. Methods: This comparative retrospective study included the clinical and pathological characteristics of (1,940) consecutive female patients who were diagnosed with invasive b

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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

Motives for public exposure to specialized sports satellite channels and the gratifications achieved about it - Research presented by (Dr. Dr. Laila Ali Jumaa), Imam Al-Kadhim College (peace be upon him) - Department of Information-2021.

       The research aims to know the extent of public exposure to specialized sports satellite channels, and what gratifications are achieved from them, and to reach scientific results that give an accurate description of exposure, motives and gratifications verified by that exposure, and the research objectives are summarized in the following:

• Revealing the habits and patterns of public exposure to specialized sports satelli

Ursolic acid (UA, 3 ?-hydroxy-urs-12-en-28-oic acid) are isomeric triterpenic acids. The high quantities of pentacyclic triterpenoids in Scabiosa species seems to be obvious and there is an evidence that most of pentacyclic triterpenoids that have been isolated are saponins. This is one of the most important characteristic of the genus Scabiosa, the main aglycones are ursolic acid and oleanolic acid. In the current study, isolation from the aerial part and roots of Scabiosa palaestina L. was performed using Preparative HPLC. Furthermore, detection and quantitation of ursolic acid was performed by high performance thin layer chromatography (HPTLC). The identification of isolated triterpenoid involves two methods including FT-IR coupl

Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.

Aim of the study:  To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).

Type of the study: a prospective analytic study

Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad