The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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.

     A novel series of pyrazole derivatives containing imidazo[1,2-a]pyridine D1-D8 moiety has been synthesized. The reaction of 2-aminopyridine with 4-phenylphenacyl bromide and 4-bromophenacyl bromide gave the products A and A1, respectively. These products then reacted with DMF and POCl₃ to obtain new aldehyde derivatives B and B1. These two aldehydes were condensed with various acetophenone substitutes to yield the corresponding chalcone derivatives C1-C10. Following this, the cycloaddition reaction with hydrazine hydrate provided new pyrazole derivatives D1-D8. The prepared compounds

Background: Soft Laser has been advantageous in medical applications and is widely used in clinical practice. It is applied because it doesn’t cause the significant thermal effects or tissue hurt when irradiated. The blood response to low power laser radiation provides information about processes of laser radiation interaction with live creatures. Objective: The aim of the current work was to evaluate the laser-induced changes of in vitro erythrocyte sedimentation rate (ESR), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC) in patients with breast cancer by irradiating a human blood sample using a green laser and comparing its effects before and after irradiation with the same power density (100mW/c

Background: One of the most important prognostic indicators in cancer is the lymph node dissection. Lymphadenectomy considered as a risk factor for deep vein thrombosis in patients with gynecological malignancy who underwent surgery. D-dimer was used to detect deep vein thrombosis, thus, it’s important to predict complications of post-operative Lymphadenectomy.

Objective: To predict the  risk of deep venous thrombosis by used serum D-dimer and wells score after pelvic lymphadenectomy in gynecological cancer.

Patients and method:  A cross sectional study conducted in Obstetrics and Gynecology/ ward in medical city, from 1^st, January 2021 to 30^th, De

Background: Polycystic ovary syndrome (PCOS) is the most common endocrinopathy affecting women, at reproductive age. PCOS is a chronic hyperandrogenic state that has many significant short-term and long-term implications for patients such as oligomenorrhea, amenorrhea, infertility, diabetes mellitus, cardiovascular disease, increased risk of endometrial cancer, and hirsutism. Objectives: To evaluate the obesity and glycemic criteria among women with polycystic ovary syndrome. Method: A case control designed study was carried out at the National Diabetes Center (NDC) / Al-Mustansiryia University; on 50 participants formed the PCOS group and 50 healthy control participants. Data collected about age, age at menarche and BMI. Also, blood sam