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Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<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 operating characteristic ROC).   Dataset was downloaded from UCI ml repository; it is composed of 9 attributes and 699 samples. The findings are clearly showing that the RBF NN classifier is the best in prediction of the type of breast tumors since it had recorded the highest performance in terms of correct classification rate (accuracy), sensitivity, specificity, and AUC (area under Receiver Operating Characteristic ROC) among all other models.</p>

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Publication Date
Tue Dec 01 2015
Journal Name
International Journal Of Current Microbiology And Applied Sciences
Expression Analysis of Salivary Microrna-31 in Oral Cancer Patients
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Oral carcinoma is the 6th most common cancer in the world. MicroRNAs are small non-coding single stranded RNAs. They have been shown to be capable of altering mRNA expression; thus some are oncogenic or tumor suppressive in nature. The salivary microRNA-31 has been proposed as a sensitive marker for oral malignancy since it was abundant in saliva more than in plasma. A total of 55 whole saliva samples were collected from 35 cases diagnosed with OC their ages and gender matched with 20 healthy subjects. TaqManq RT-PCR was performed for RNA samples. Mean age was 52.23+13.73 years in cases (range:17-70 years) with male predominance represented 69%. Risk of smoking and alcoholism was highly significant. The median fold change of miR-31 was sign

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Publication Date
Thu Feb 01 2024
Journal Name
Computers In Biology And Medicine
Model based smooth super-twisting control of cancer chemotherapy treatment
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Chemotherapy is one of the most efficient methods for treating cancer patients. Chemotherapy aims to eliminate cancer cells as thoroughly as possible. Delivering medications to patients’ bodies through various methods, either oral or intravenous is part of the chemotherapy process. Different cell-kill hypotheses take into account the interactions of the expansion of the tumor volume, external drugs, and the rate of their eradication. For the control of drug usage and tumor volume, a model based smooth super-twisting control (MBSSTC) is proposed in this paper. Firstly, three nonlinear cell-kill mathematical models are considered in this work, including the log-kill, Norton-Simon, and hypotheses subject to parametric uncertainties and exo

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Publication Date
Fri Jan 01 2021
Journal Name
Materials Today: Proceedings
In silico analysis of quercetin as potential anti-cancer agents
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Publication Date
Wed Jan 30 2019
Journal Name
International Journal Of Applied Pharmaceutics
THE IMPACT OF NEW TARGETING METHODS IN THE CANCER THERAPY
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Rapid development has achieved in treating tumor to stop malignant cell growth and metastasis in the past decade. Numerous researches have emerged to increase potency and efficacy with novel methods for drug delivery. The main objective of this literature review was to illustrate the impact of current new targeting methods to other previous delivering systems to select the most appropriate method in cancer therapy. This review first gave a brief summary of cancer structure and highlighted the main roles of targeting systems. Different types of delivering systems have been addressed in this literature review with focusing on the latest carrier derived from malarial protein. The remarkable advantages and main limitations of the later

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Publication Date
Sat Jun 19 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Alteration of Serum Immunoglobulin Levels in Woman with Ovarian Cancer
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Ovarian cancer has a high mortality and delayed diagnosis. Several immunological alterations take place during ovarian carcinogenesis, and can be of value in the surveillance of the diseases. This research was conducted to evaluate serum immunoglobulin levels in women with ovarian cancer and to assess their role in disease process. The present study is composed of 85 women (mean age = 62.03±12.4 yrs) with clinically and pathologically confirmed ovarian cancer and 65 healthy females as a control group (mean age = 61±12.1 yrs). ELISA test was achieved for the determination of serum [IgG, IgA, IgM]. The findings of current study illustrated significant (P=0.001) increase in serum IgG, IgA, and IgM levels as compared to co

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Publication Date
Mon Jan 01 2024
Journal Name
Brazilian Dental Science
Evaluation of flexural strength and degree of conversion of temporary crown materials at different aging periods in artificial saliva
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Objective: Evaluate the effects of different storage periods on flexural strength (FS) and degree of conversion (DC) of Bis-Acryl composite and Urethane dimethacrylate provisional restorative materials. Material and Methods: A total of 60 specimens were prepared from four temporary crown materials commercially available and assigned to four tested groups (n = 15 for each group): Prevision Temp, B&E CROWN, Primma Art, and Charm Temp groups. The specimens were stored in artificial saliva, and the FS was tested after 24 h, 7 d, and 14 d. A standard three-point bending test was conducted using a universal testing machine. Additionally, the DC was determined using a Fourier transform infrared spectroscopy (FTIR) device. The data were analyzed st

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Publication Date
Tue Nov 06 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
The Impact of An Education Program upon Women's Knowledge in Managing Breast Self–Examination
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Objective: To find out if there are any significant differences between these women's knowledge in the
management of Breast Self-Examination in study and control group regarding some variables.
Methodology: A quasi-experimental design was used. A purposive "non-probability" sample of (260) women who
are employee and students in both colleges (Nursing and Health and Medical Technologies) was selected. The
sample consists of two groups, experimental group (130) includes those in (Nursing college), and control group
(130) in (Health and Medical Technologies). A questionnaire was constructed which included demographic
information, reproductive information, family history, previous medical history, and information about wome

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Ultrasound Guided Core Needle Biopsy in The Diagnosis of Suspicious Breast Lesions: Radiologist’s perspectives
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Background: Ultrasound guided core needle biopsy is becoming a gold standard in the work up of suspicious breast lesion. In Iraq, radiologists are not taking the lead in core needle biopsy performance.

Objectives: To evaluate the radiologist performance of core needle biopsy highlighting the precession and accuracy of the procedure, the concordance of ultrasound and histopathology, and identifying challenges facing the radiologist during the procedure.

Subjects and Methods: A prospective study involving a total of 50 patients with ultrasound (US) BIRADS IV or V.  Ultrasound guided core needle biopsy was performed for each patient. Surgical pathol

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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Publication Date
Sat Oct 02 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Using the wavelet analysis to estimate the nonparametric regression model in the presence of associated errors
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Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

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