received the M.Sc. degree in Information Engineering from AL-Nahrain University, Iraq. His research interests include ML, Computer programming, image processing, and AI. He is working as responsible for the website division\ at the University of Baghdad. Having more than 20 research papers in different fields.
EDUCATION
M.Sc. in Information Engineering
RESEARCH, TEACHING, or OTHER INTERESTS
Artificial Intelligence, Information Systems, Human-Computer Interaction, Computer Vision and Pattern Recognition
Enhancement of Recommendation Engine Technique for Bug System Fixes Jalal Sadoon Hameed Al-Bayati, Mohammed Al-Shamma, Furat Nidhal Tawfeeq Journal of Advances in Information Technology, 2024 — This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers.
CORRELATION BETWEEN ULTRASOUND BI-RADS 4 BREAST LESIONS AND FINE NEEDLE CYTOLOGY CATEGORIES IN A SAMPLE OF IRAQI FEMALE PATIENTS Hiba Mohammed Abdulwahid, Zahraa Mohammed Yahya, Furat Nidhal, Farah A.J. AL Zahwi, Muna Jumaa Ali Experimental and Applied Biomedical Research Eabr, 2023 Breast cancer is the most common malignancy in female and the most registered cause of women’s mortality worldwide. BI-RADS 4 breast lesions are associated with an exceptionally high rate of benign breast pathology and breast cancer, so BI-RADS 4 is subdivided into 4A, 4B and 4C to standardize the risk estimation of breast lesions. The aim of the study: to evaluate the correlation between BI-RADS 4 subdivisions 4A, 4B & 4C and the categories of reporting FNA cytology results. A case series study was conducted in the Oncology Teaching Hospital in Baghdad from September 2018 to September 2019. Included patients had suspicious breast findings and given BI-RADS 4 (4A, 4B, or 4C) in the radiological report accordingly. Fine needle aspiration was performed under the ultrasound guide and the results were classified into five categories. The biopsy was performed for suspicious, malignant or equivocal FNA findings. This study included 158 women with BI-RADS 4 breast lesions with the mean age of (44.6 years); There was a highly significant association between BI-RADS 4 breast lesion and FNA results (p<0.001); 51.9% of BI-RADS IV-C had C5 FNA results. There was a highly significant association between BI-RADS 4 lesion and the final diagnosis (p<0.001); 41.2% of BI-RADS 4 B had a malignant breast lesion, while 37.3% of BI-RADS 4 C had a malignant lesion. A clear relationship was observed between BI-RADS 4 subcategories and the fine needle aspiration cytology subgroups. BI-RADS 4-B is helpful in the discrimination between benign and malignant breast lesions; furthermore BI-RADS 4C has more acceptable validity in the diagnosis of breast malignancy. Therefore, BI-RADS subcategories are encouraged to be included and mentioned in the ultrasound report for more accurate estimation of the lesion nature.
Using User Experience Metrics for Academic Management System of University of Baghdad Furat Nidhal Tawfeeq, Jalal Sadoon Hameed Al-Bayati, Mohammed Al-Shammaa 2023 3rd International Scientific Conference of Engineering Sciences Isces 2023 Proceedings, 2023 Interface evaluation has been the subject of extensive study and research in human-computer interaction (HCI). It is a crucial tool for promoting the idea that user engagement with computers should resemble casual conversations and interactions between individuals, according to specialists in the field. Researchers in the HCI field initially focused on making various computer interfaces more usable, thus improving the user experience. This study's objectives were to evaluate and enhance the user interface of the University of Baghdad's implementation of an online academic management system using the effectiveness, time-based efficiency, and satisfaction rates that comply with the task questionnaire process. We made a variety of interfaces for the system's interface and selected the best ones based on the study's findings. This study will show how user-friendly our interface will be for those with little to no computer experience. 24 participants participated in the usability testing to evaluate the system's functionality. The results demonstrate excellent usability with a participation error rate of 33.3% and an efficacy rate of 71.43%. Furthermore, some suggestions are given for enhancing our university system's human-computer interaction metrics.
Reduced hardware requirements of deep neural network for breast cancer diagnosis Yasmine M. Tabra, Furat N. Tawfeeq Iaes International Journal of Artificial Intelligence, 2022 Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration on each subsystem to futher reduce the hardware requirements. The DNN was designed using a system generator and implemented using very hardware description language (VHDL). The system achievments outcomes the superior’s accuracy rate of approximately 99.6 percent in distinguishing bengin from malignant tissue. Also, the hardware resources were reduced by 30 percent from works of literature with an error rate of 7e-4 when using the Kintex-7 xc7k325t-3fbg676 board.
Comparison of clinico-pathological presentations of triple-negative versus triple-positive and HER2 iraqi breast cancer patients Nada A. S. Alwan, Furat N. Tawfeeq Open Access Macedonian Journal of Medical Sciences, 2019 BACKGROUND: Breast cancer remains the most common malignancy among the Iraqi population. Affected patients exhibit different clinical behaviours according to the molecular subtypes of the tumour.
 AIM: To identify the clinical and pathological presentations of the Iraqi breast cancer subtypes identified by Estrogen receptors (ER), Progesterone receptors (PR) and HER2 expressions.
 PATIENTS AND METHODS: The present study comprised 486 Iraqi female patients diagnosed with breast cancer. ER, PR and HER2 contents of the primary tumours were assessed through immunohistochemical staining; classifying the patients into five different groups: Triple Negative (ER/PR negative/HER2 negative), Triple Positive (ER/PR positive/HER2 positive), Luminal A (ER/PR positive/HER2 negative), HER2 enriched ((ER/PR negative/HER2 positive) and all other subtypes.
 RESULTS: The major registered subtype was the Luminal A which was encountered in 230 patients (47.3%), followed by the Triple Negative (14.6%), Triple Positive (13.6%) and HER2 Enriched (11.5%). Patients exhibiting the Triple Negative subtype were significantly younger than the rest of the groups and presented with larger size tumours. A significant difference in the distribution of the breast cancer stages was displayed (p < 0.05); the most advanced were noted among those with HER2 enriched tumours who exhibited the highest frequency of poorly differentiated carcinomas and lymph node involvement.
 CONCLUSION: The most significant variations in the clinicopathological presentations were observed in the age and clinical stage of the patients at diagnosis. Adoption of breast cancer molecular subtype classification in countries with limited resources could serve as a valuable prognostic marker in the management of aggressive forms of the disease.
Optimization of digital histopathology image quality Furat Nidhal Tawfeeq, Nada A.S. Alwan, Basim M. Khashman Iaes International Journal of Artificial Intelligence, 2018 <span lang="EN-US">One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues. These were implemented by defining membership functions between colours range using MATLAB. Results: 50 histopathological images were tested on four types of membership functions (MF); the results show that (nine-triangular) MF get 75.4% correctly predicted pixels versus 69.1, 72.31 and 72% for (five- triangular), (five-Gaussian) and (nine-Gaussian) respectively. Conclusions: In line with the era of digitally driven e-pathology, this process is essentially recommended to ensure quality interpretation and analyses of the processed slides; thus overcoming relevant limitations.</span>
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels FNT Yasmine M. Tabra International Journal of Intelligent Engineering and Systems 19 (1), 321-334 , 2026 2026
Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata MAS Jalal Sadoon Hameed Al-Bayati, Furat Nidhal Tawfeeq Journal of Advances in Information Technology 16 (11), 1604-1623 , 2025 2025
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation through a Hybrid Methodology JSHAB Furat Nidhal Tawfeeq, Mohammed Al-Shammaa Pattern Recognition and Artificial Intelligence 1393, 325–341 , 2025 2025
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features FNT Yasmine M. Tabra International Journal of Advanced Technology and Engineering Exploration … , 2025 2025
Enhancement of Recommendation Engine Technique for Bug System Fixes MAS Furat Nidhal Tawfeeq, Jalal Sadoon Hameed Al-Bayati Journal of Advances in Information Technology 15 (4), 555-564 , 2024 2024 Citations: 2
Using User Experience Metrics for Academic Management System of University of Baghdad MAS Furat Nidhal Tawfeeq, Jalal Sadoon Hameed Al-Bayati 2023 3rd International Scientific Conference of Engineering Sciences (ISCES) , 2023 2023 Citations: 1
Reduced hardware requirements of deep neural network for breast cancer diagnosis FNT Yasmine M. Tabra IAES International Journal of Artificial Intelligence (IJ-AI) 11 (4), 1362-1372 , 2022 2022 Citations: 6
Correlation Between Ultrasound BI-RADS 4 Breast Lesions and Fine Needle Cytology Categories in a Sample of Iraqi Female Patients MJA Hiba Mohammed Abdulwahid , Zahraa Yahya Mohammed , Furat Nidhal Tawfeeq ... Serbian Journal of Experimental and Clinical Research , 2021 2021 Citations: 1
Breast cancer stage at the time of presentation: clinicopathological correlations N Alwan, F Tawfeeq, M Maallah, S Sattar HMMS 2021 (4), 41-53 , 2021 2021 Citations: 2
Comparison of Clinico-Pathological Presentations of Triple-Negative versus Triple-Positive and HER2 Iraqi Breast Cancer Patients NAS Alwan, FN Tawfeeq Open access Macedonian journal of medical sciences 7 (21), 3534 , 2019 2019 Citations: 9
Improvement of Alert System against Tampering and Theft in Surveillance Cameras FN Tawfeeq Tikrit Journal of Pure Science 24 (2), 98-103 , 2019 2019
Demographic and clinical profiles of female patients diagnosed with breast cancer in Iraq. NAS Alwan, FN Tawfeeq, NAG Mallah Journal of Contemporary Medical Sciences 5 (1) , 2019 2019 Citations: 96
Assessing the Period between Diagnosis of Breast Cancer and Surgical Treatment among Mastectomized Female Patients in Iraq FY Nada A. S. Alwan, Furat N Tawfeeq, Safana A. Sattar International Journal of Medical Research & Health Sciences 8 (1), 43-50 , 2019 2019 Citations: 10
Development of Prognosis Factors in a Scoring System for Predicting of Breast Cancer Mortality FN Tawfeeq Journal of Information Engineering and Applications 8 (4), 43-50 , 2018 2018 Citations: 2
Optimization of Digital Histopathology Image Quality FN Tawfeeq, NAS Alwan, BM Khashman IAES International Journal of Artificial Intelligence (IJ-AI) 7 (2) , 2018 2018 Citations: 3
Comparative Study on the Clinicopathological Profiles of Breast Cancer Among Iraqi and British Patients NAS Alwan, D Kerr, D Al-Okati, F Pezella, FN Tawfeeq The Open Public Health Journal 11, 177-191 , 2018 2018 Citations: 67
Clinical and Pathological Characteristics of Triple Positive Breast Cancer among Iraqi Patients SN Nada A.S.Alwan, Faisal H. Mualla, Munawar Al Naqash, Saad Kathum, Furat N ... Gulf Journal of Oncology, 51-60 , 2017 2017 Citations: 33
Breast cancer subtypes among Iraqi patients: identified by their Er, Pr and Her2 Status NAS Alwan, FN Tawfeeq, FH Muallah Journal of the Faculty of Medicine Baghdad 59 (4), 303-307 , 2017 2017 Citations: 26
A POWERFUL AUTOMATED IMAGE INDEXING AND RETRIEVAL TOOL FOR SOCIAL MEDIA Sample N Ahmed, A Morad, FN Tawfeeq International Research Journal of Engineering and Technology 4 (9), 1118-1123 , 2017 2017
The stage of breast cancer at the time of diagnosis: correlation with the clinicopathological findings among Iraqi patients NAS Alwan, F Tawfeeq, AS Maallah, SA Sattar, WA Saleh J Neoplasm 2 (3), 22 , 2017 2017 Citations: 57
MOST CITED SCHOLAR PUBLICATIONS
Knowledge, attitude and practice regarding breast cancer and breast self-examination among a sample of the educated population in Iraq TFN Alwan NA, Al-Attar WM, Eliessa RA, Madfaie ZA Eastern Mediterranean Health Journal 18 (4), 337-345 , 2012 2012 Citations: 158
Demographic and clinical profiles of female patients diagnosed with breast cancer in Iraq. NAS Alwan, FN Tawfeeq, NAG Mallah Journal of Contemporary Medical Sciences 5 (1) , 2019 2019 Citations: 96
Comparative Study on the Clinicopathological Profiles of Breast Cancer Among Iraqi and British Patients NAS Alwan, D Kerr, D Al-Okati, F Pezella, FN Tawfeeq The Open Public Health Journal 11, 177-191 , 2018 2018 Citations: 67
The stage of breast cancer at the time of diagnosis: correlation with the clinicopathological findings among Iraqi patients NAS Alwan, F Tawfeeq, AS Maallah, SA Sattar, WA Saleh J Neoplasm 2 (3), 22 , 2017 2017 Citations: 57
Clinical and Pathological Characteristics of Triple Positive Breast Cancer among Iraqi Patients SN Nada A.S.Alwan, Faisal H. Mualla, Munawar Al Naqash, Saad Kathum, Furat N ... Gulf Journal of Oncology, 51-60 , 2017 2017 Citations: 33
Breast cancer subtypes among Iraqi patients: identified by their Er, Pr and Her2 Status NAS Alwan, FN Tawfeeq, FH Muallah Journal of the Faculty of Medicine Baghdad 59 (4), 303-307 , 2017 2017 Citations: 26
Real Time Motion Detection in Surveillance Camera Using MATLAB FN Tawfeeq International Journal of Advanced Research in Computer Science and Software … , 2013 2013 Citations: 11
Assessing the Period between Diagnosis of Breast Cancer and Surgical Treatment among Mastectomized Female Patients in Iraq FY Nada A. S. Alwan, Furat N Tawfeeq, Safana A. Sattar International Journal of Medical Research & Health Sciences 8 (1), 43-50 , 2019 2019 Citations: 10
Gate Control System for New Iraqi License Plate YMT FN Tawfeeq Iraqi Journal for Computers and Informatics 1 (1), 1-2 , 2014 2014 Citations: 10
Knowledge and practices of women in Iraqi universities on breast self examination NAS Alwan, WM Al-Attar, RA Eliessa, ZA Madfaie, FN Tawfeeq EMHJ 18 (7), 742-748 , 2012 2012 Citations: 10
Comparison of Clinico-Pathological Presentations of Triple-Negative versus Triple-Positive and HER2 Iraqi Breast Cancer Patients NAS Alwan, FN Tawfeeq Open access Macedonian journal of medical sciences 7 (21), 3534 , 2019 2019 Citations: 9
Reduced hardware requirements of deep neural network for breast cancer diagnosis FNT Yasmine M. Tabra IAES International Journal of Artificial Intelligence (IJ-AI) 11 (4), 1362-1372 , 2022 2022 Citations: 6
Network Congestion and Quality of Service Analysis Using OPNET FN Tawfeeq Thesis, Department of Information Engineering, Al-Nahrain University , 2009 2009 Citations: 6
Optimization of Digital Histopathology Image Quality FN Tawfeeq, NAS Alwan, BM Khashman IAES International Journal of Artificial Intelligence (IJ-AI) 7 (2) , 2018 2018 Citations: 3
Enhancement of Recommendation Engine Technique for Bug System Fixes MAS Furat Nidhal Tawfeeq, Jalal Sadoon Hameed Al-Bayati Journal of Advances in Information Technology 15 (4), 555-564 , 2024 2024 Citations: 2
Breast cancer stage at the time of presentation: clinicopathological correlations N Alwan, F Tawfeeq, M Maallah, S Sattar HMMS 2021 (4), 41-53 , 2021 2021 Citations: 2
Development of Prognosis Factors in a Scoring System for Predicting of Breast Cancer Mortality FN Tawfeeq Journal of Information Engineering and Applications 8 (4), 43-50 , 2018 2018 Citations: 2
Using User Experience Metrics for Academic Management System of University of Baghdad MAS Furat Nidhal Tawfeeq, Jalal Sadoon Hameed Al-Bayati 2023 3rd International Scientific Conference of Engineering Sciences (ISCES) , 2023 2023 Citations: 1
Correlation Between Ultrasound BI-RADS 4 Breast Lesions and Fine Needle Cytology Categories in a Sample of Iraqi Female Patients MJA Hiba Mohammed Abdulwahid , Zahraa Yahya Mohammed , Furat Nidhal Tawfeeq ... Serbian Journal of Experimental and Clinical Research , 2021 2021 Citations: 1
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels FNT Yasmine M. Tabra International Journal of Intelligent Engineering and Systems 19 (1), 321-334 , 2026 2026
