Preferred Language
Articles
/
veblFJ8BmraWrQ4d-2tr
Effective SMOTE boost with deep learning for IDC identification in whole-slide images
...Show More Authors

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.

Scopus Crossref
View Publication
Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Isolation and identification of polyhydroxyalkanoates producing bacteria from biopolymers waste in soil
...Show More Authors
Abstract<p>The production of polyhydroxyalkanoates PHAs from biopolymer degrading bacteria was examined <italic>in situ</italic> by screening isolates using Sudan B Black staining process as potential PHAs detecting, and Nile Blue staining as a proof method detection. Five bacterial strains isolated from biopolymer waste buried in a garden soil were able to produce high rate of PHA. <italic>AK1P</italic> and <italic>AK2P</italic> strains demonstrated high productivity of biopolymer by converting 5% (w/v) lactose as the only carbon source to PHA during fermentation. <italic>AY2P</italic> strain converted 5% (w/v) of glucose with less PHA accumulation. The f</p> ... Show More
View Publication
Scopus (5)
Crossref (4)
Scopus Crossref
Publication Date
Wed Mar 16 2016
Journal Name
World Journal Of Pharmaceutical Research
Identification of some species of wireworm Agriotes spp.(Coleoptera: Elateridae) in Baghdad
...Show More Authors

Publication Date
Sun Jan 01 2017
Journal Name
World Journal Of Pharmaceutical Research
IDENTIFICATION OF SOME SPECIES OF WIREWORM AGRIOTES SPP. (COLEOPTERA: ELATERIDAE) IN BAGHDAD
...Show More Authors

Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Identification of the main causes of risks in engineering procurement construction projects
...Show More Authors
Abstract<p>Many risks have adverse consequences for construction projects’ objectives such as quality, schedule, and cost. As engineering procurement construction (EPC) contracts gradually become one of the most common types used in implementing major large-scale construction projects, identifying common risk types and analyzing their root causes is important for developing measures to decrease and eliminate future risks in these types of contracts. The information about the main causes of risks was collected <italic>via</italic> well-structured questionnaires addressed to construction sector professionals and preparing lists of main potential risks in EPC/construction projects throu</p> ... Show More
View Publication
Crossref (4)
Crossref
Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Educational And Psychological Researches
The relationship between critical thinking, epistemological beliefs, and learning strategies with the students’ academic performance
...Show More Authors

The present study was conducted to investigate the relationship between critical thinking, epistemological beliefs, and learning strategies with the academic performance of high school first-grade male and female students in Yazd. For this purpose, from among all first-grade students, as many as 250 students (130 females and 120 males) were selected by using multistage cluster sampling. The data needed were then collected through using California Critical Thinking Skills Test, Schommer's Epistemological Beliefs Questionnaire, Biggs’ Revised Two Factor Study Process Questionnaire. The findings indicated that there is a positive significant relationship between critical thinking and academic performance and achievement. Moreover, four fa

... Show More
View Publication Preview PDF
Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
...Show More Authors

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

... Show More
View Publication Preview PDF
Scopus (14)
Crossref (8)
Scopus Clarivate Crossref
Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Comparison between Different Data Image Compression Techniques Applied on SAR Images
...Show More Authors

In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.

View Publication Preview PDF
Publication Date
Tue Sep 19 2017
Journal Name
Al-academy
Process of artistic conception of nature's images Between becoming and buration
...Show More Authors

This research deals with process of artistic conception of nature's images between becoming and buration, as an attempt to transfer the philosophical concepts to art via it's structural applications in forming the picture, due to the importance of these concepts which might be engaged with the vision of the artist in his own and subjective contention with the nature. The research consists of four chapters, first one included the problem of the research, importance, need to the research and the aim of the research represented by process of artistic conception of nature's images between becoming  and buration. Also included the limits of research and most important terms. Second chapter included theoretical frame that consists of thre

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri May 05 2017
Journal Name
International Journal Of Science And Research (ijsr)
Automatic brain tumor segmentation from MRI images using region growing algorithm
...Show More Authors

LK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2

View Publication
Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest
...Show More Authors

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

... Show More
View Publication Preview PDF
Scopus (17)
Crossref (15)
Scopus Crossref