Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolutional Neural Network (CNN) technology to detect areas impacted by Invasive Ductal Carcinoma (IDC) in whole slide pictures. The trials used a dataset of 162 individuals with IDC, split into training (113 photos) and testing (49 images) groups. Every model was subjected to individual testing. The SMO_CNN model we developed demonstrated exceptional testing and training accuracies of 98.95% and 99.20% respectively, surpassing CNN, VGG19, and ResNet50 models. The results highlight the effectiveness of the created model in properly detecting IDC-affected tissue areas, showing great promise for improving breast cancer diagnosis and treatment planning. We surpassing other models as such, CNN, VGG19, ResNet50.
The research aims to design an electronic program that allows users to assess the possibility of different practices for projects management professional according to the PMBOK methodology)) and using the requirements Data mentioned in the "knowledge and experience in project management Evaluation guide" issued by the professional Institute of project management According to the results of this program will be electronic The possible classification of project management in terms of both (proficiency_ perform tasks) as less than the desired level or within or above average in terms of best practices, and finally a number of recommendations to overcome the possible shortcomings. The most important is the need to enrich the service
... Show MoreFlexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best
... Show MorePsoriasis is a complex autoimmune disorder characterized by skin inflammation with keratinocyte proliferation, and 85% of cases present as plaque-type psoriasis. Biologics such as ustekinumab (UST) are highly successful therapies for psoriasis. To achieve maximum clinical efficacy while minimizing undesirable effects, therapeutic drug monitoring (TDM) for biologics has emerged. This study aims to measure the UST trough level (TL) and anti-drug antibodies (ADAs) and to evaluate clinical response in Iraqi patients with moderate-to-severe psoriasis in order to make appropriate recommendations for modifying therapy. This cross-sectional study enrolled 75 patients, divided into two groups: Group 1, patients who achieved the UST target TL (≥0.6
... Show MoreObjective(s): To assess the eating habits of adolescent females with iron deficient anemia.
Methodology: This study employed a quantitative research, descriptive evaluation design.The study was carried out on adolescent girls attending Kirkuk secondary school, period from 11 April to 27 December 2022. A non- probability (Purposive) sample has been applied to obtain the study goals. The study sample was (62) student who participate in the study.
Results: Pre-test results from the study revealed that 54.8% of students had moderate IDA. While the students' iron levels returned to normal in the posttest (53.2%). The majority of students (59.7%) had poor eatin
... Show MoreThe formal investigation of the interior spaces of the residential bedrooms for children with autism is one of the basic tasks that should be known by the interior designer. Achieving an atmosphere compatible with his health condition, which contributes to generating a sense of spatial intimacy through the design dimension provided by the interior designer and his tireless endeavor to meet the needs of the child in an internal environment that achieves the functional dimension and spiritual approaches that enhance the child’s sense of spatial belonging and contribute to improving his mood and this positively reflects on his behavior and social integration. The current research has reached the most important design criteria that must be
... Show MoreThe aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.
A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network
... Show MoreThis paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ
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