Dilber Uzun Ozsahin

• Phd
• Professor (Associate) at University of Sharjah and Near East University

Breast cancer (BC) is the second most common cause of cancer in women and the most common kind of cancer diagnosed with high mortality rate. This heterogeneous disease is classified into multiple subtypes based on the expression of key biomarkers, including human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone re...

Annually, influenza viruses cause a considerable number of deaths worldwide and are a primary cause of severe respiratory diseases. Finding novel immunogenic locations that might trigger a potent immune response is therefore crucial. The present study utilized bioinformatics techniques to develop mRNA and multiepitope-based vaccinations specificall...

Background Pancreatic cancer is the deadliest form of cancer with a low survival rate due to its late diagnosis. Hence, early detection and swift intervention are very crucial for its management. However, the current diagnostic markers lack sufficient precision, and the effectiveness of treatment options remains imprecise, emphasizing the need for...

In this article, we propose a new modified projection and contraction algorithm for approximating solutions of a variational inequality problem involving a quasi-monotone and Lipschitz continuous mapping in real Hilbert spaces. We incorporate the technique of two-step inertia into a single projection and contraction method and prove a weak converge...

Prostate cancer is a leading cause of cancer-related morbidity and mortality worldwide, with diagnostic challenges magnified in underrepresented regions like sub-Saharan Africa. This study introduces a novel application of ConvNeXt, an advanced convolutional neural network architecture, for multi-class classification of prostate histopathological i...

Objectives: The objective of the present study was to determine the accuracy of machine learning (ML) models in the detection of mesiobuccal (MB2) canals in axial cone-beam computed tomography (CBCT) sections. Methods: A total of 2500 CBCT scans from the oral radiology department of University Dental Hospital, Sharjah were screened to obtain 277 hi...

Chronic Hepatitis B Virus (HBV) infection remains a formidable global health challenge, driving severe liver complications such as hepatocellular carcinoma (HCC) and pyogenic liver abscesses (PLA). At the core of HBV persistence lies covalently closed circular DNA (cccDNA), a viral reservoir that fuels ongoing infection despite antiviral treatments...

Anesthesia is used as a neural blocker capable of preventing nociceptive impulses from enteringthe nervous system, before, during, and after surgery. Anesthetic agents should be able to enhance recovery processes, potencies, and relaxation of the muscles, including a wide range of safety, free from toxicity, reactivity problems, and possibilities o...

This review explores the green biosynthesis of nanoparticles using plant extracts, emphasizing the underlying mechanisms, recent advancements, challenges, and diverse applications of this sustainable technology. Plant-mediated nanoparticle synthesis presents an eco-friendly and cost-effective alternative to conventional methods that often rely on t...

Accessory ostium [AO] is one of the important anatomical variations in the maxillary sinus. AO is often associated with sinus pathology. Radiographic imaging plays a very important role in the detection of AO. Deep learning models have been used in maxillofacial imaging for interpretation and segmentation. However, there have been no research paper...

Signalling of calcium ions is vital for the normal physiology and survival of cells. Membrane bound organelles like the mitochondria and many other cell-bound proteins and receptors play significant roles in regulating intracellular calcium levels thus maintaining homeostasis of the external and internal cell environments. The regulation of cellula...

Background Pneumatization of turbinates, also known as concha bullosa (CB), is associated with nasal septal deviation and sinonasal pathologies. This study aims to evaluate the performance of deep learning models in detecting CB in coronal cone-beam computed tomography (CBCT) images. Methods Standardized coronal images were obtained from 203 CBCT...

Wastewater treatment is a critical solution that decreases environmental effects by removing organic waste and producing a sustainable water source. However, the fundamental issue in running a wastewater treatment plant is the excess chemical oxygen demand concentration due to sludge thickening. The quality of the WWTP's effluent water will decreas...

Key Objective Develop a ConvNeXt-based deep learning model for AML subtype classification using high-resolution blood smear images. Compare ConvNeXt’s performance with traditional CNNs (ResNet50) and Vision Transformers to assess classification accuracy and feature extraction. Enhance model generalization and stability using Stochastic Weight Avera...

The purpose of this paper is to investigate the existence of the integral solution of a fractional dynamic problem in the domain of time scale calculus. The discussion has been done with the help of Schauder’s fixed point theorem and the Kolmogorov compactness criterion in time scales. The new notion of the Caputo derivative in terms of nabla deriv...

Precise rainfall forecasting is essential for efficient water resource management and disaster preparedness, especially in areas vulnerable to severe weather conditions. This study presents an integrated approach, combining machine learning techniques and statistical models, to predict rainfall patterns in Bangladesh's southwestern and northwestern...

Acute Myeloid Leukemia (AML) is a complex hematologic malignancy where precise subtype classification is critical for targeted treatment and improved patient outcomes. This study explores the potential of ConvNeXt, an advanced convolutional neural network architecture, for high-resolution peripheral blood smear image classification into AML subtype...

In recent decades, rapid development has exacerbated climate challenges, posing serious threats to ecological sustainability. To address these issues, renewable energy, ICT technologies, financial development, and globalization have emerged as essential tools for mitigating ecological impacts and fostering green economic growth. These measures alig...

Robotic bariatric surgery (RBS) uses robotics in weight loss operations. The robotic system has been tremendous in the field of bariatric surgery (BS) owing to its overwhelming advantages. As a result, surgeons perform RBS by controlling robotic arms equipped with surgical equipment from a console. In this study, our focus is to evaluate the BS dat...

Background The rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students’ perceptions regarding the credibility and effectiveness of AI as a learning tool and to explore the dynamics...

In the pursuit of environmental sustainability, numerous countries, including the United States, are adjusting their policy frameworks to mitigate ecological degradation. This study explores the key drivers of load capacity factor (LF) from 1980 to 2021, with LF serving as a reliable proxy for ecological quality, as it reflects both the demand and...

This review paper analyzes recent advancements in bio-polymer coatings for probiotic microencapsulation, with a particular emphasis on chitosan and its synergistic combinations with other materials. Probiotic microencapsulation is essential for protecting probiotics from environmental stresses, enhancing their stability, and ensuring effective deli...

Developing an efficient and reliable intelligent approach to the available groundwater (GW) resources appears crucial for achieving Saudi Vision 2030 on the availability of freshwater resources, the prosperity of people, and economic development. The present study is based on a real-field investigation and experimental analysis using ion chromatogr...

Background Radiographs play a key role in diagnosis of periodontal diseases. Deep learning models have been explored for image analysis in periodontal diseases. However, there is lacuna of research in the deep learning model-based detection of furcation involvements [FI]. The objective of this study was to determine the accuracy of deep learning mo...

Background Cardiovascular diseases (CVDs) continue to be the world’s greatest cause of death. To evaluate heart function and diagnose coronary artery disease (CAD), myocardial perfusion imaging (MPI) has become essential. Artificial intelligence (AI) methods have been incorporated into diagnostic methods such as MPI to improve patient outcomes in r...

Dynare is a popular software for solving dynamic stochastic general equilibrium (DSGE) and overlapping generations (OLG) models. It is used along with Octave or Matlab. However, writing documents using Dynare outputs can be error-prone and time-consuming, as it requires copying and pasting the outputs into the document. To address this problem and...

While COVID-19 is no longer the main public health challenge, we should still exercise caution. The rapid spread of the virus in the past presented a significant threat to public health, highlighting the need for continued vigilance and effective preventive measures. Over the years, science-related groups, institutions, healthcare services, schools...

Climate change occurs as a result of the consistent alterations of the normal atmospheric weather conditions that result in an imbalance of the earth’s climate, caused by the radiations from chemical, biological, or natural sources, leading to an increased surface temperature that is capable of causing an intense threat to human's life, plants, ani...

Radiological examinations are carried out in various departments of a hospital along with the radiology department. This involves the involvement of nurses also during the radiological procedures. Therefore, there is a high probability of radiation exposure to the nurses as well. This study aimed to understand the awareness and practice of radiolog...

The scarcity of medical imaging datasets and privacy concerns pose significant challenges in artificial intelligence-based disease prediction. This poses major concerns to patient confidentiality as there are now tools capable of extracting patient information by merely analyzing patient’s imaging data. To address this, we propose the use of synthe...

Abstract The prediction of CO2 emissions is critical for designing sustainable environmental policies and meeting the Sustainable Development Goals, particularly those related to climate action. Therefore, this paper aims to assess the appropriate predictive model for tracking carbon emissions in four African economies with the highest carbon emis...

In this study, we investigate the symmetry analysis and explicit solutions for the Estevez–Mansfield–Clarkson (EMC) equation. Our main objectives are to identify the Lie point symmetries of the EMC equation, construct an optimal system of one-dimensional subalgebras, and reduce the EMC equation to a set of ordinary differential equations (ODEs). We...

Background: Artificial intelligence (AI) models are being increasingly studied for the detection of variations and pathologies in different imaging modalities. Nasal septal deviation (NSD) is an important anatomical structure with clinical implications. However, AI-based radiographic detection of NSD has not yet been studied. Objective: This resear...

Coronary Artery Disease (CAD) is a global health concern, with diagnostic modalities and risk factors that exhibit regional variations. This study, conducted at the Islamabad Diagnostic Center, Pakistan, aimed to provide a comprehensive assessment of CAD prevalence, severity, and associated risk factors, while also evaluating the diagnostic accurac...

Developing an efficient and reliable intelligent approach to the available groundwater (GW) resources appears crucial for achieving Saudi Vision 2030 on the availability of freshwater resources, the prosperity of people, and economic development. The present study is based on a real-field investigation and experimental analysis using ion chromatogr...

The Inertial Tseng Algorithm (ITA) and the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) are well-established methods that provide effective ways to approximate zeros of the sum of monotone operators. In this study, we applied both ITA and FISTA in the restoration process of prostate cancer and osteosarcoma images that were degraded with...

It is well-known that the Tseng algorithm and its modifications have been successfully employed in approximating zeros of the sum of monotone operators. In this study, we restored various thoracic diseases’ computerized tomography (CT) images, which were degraded with a known blur function and additive noise, using a modified Tseng algorithm. The t...

For herbal and modern drug research, secondary metabolites produced by plants are a valuable source of pharmaceutically active compounds. Northern Nigeria relies heavily on plants as a source of medication. Succulent perennial herb Bryophyllum pinnatum is endemic to Africa and Asia. The current study investigates the in vitro pharmacological potent...

Disease prediction is greatly challenged by the scarcity of datasets and privacy concerns associated with real medical data. An approach that stands out to circumvent this hurdle is the use of synthetic data generated using Generative Adversarial Networks (GANs). GANs can increase data volume while generating synthetic datasets that have no direct...

This study explored the application of machine learning in predicting post-treatment outcomes for chronic neck pain patients undergoing a multimodal program featuring cervical extension traction (CET). Pre-treatment demographic and clinical variables were used to develop predictive models capable of anticipating modifications in cervical lordotic a...

Heart failure is a progressive disease that leads to high mortality rates if left untreated, and inotropes are a class of drugs used to treat a type of heart failure where patients have reduced ejection fraction (HFrEF). This study aims to utilize the Fuzzy-Preference Ranking Organization Method for Enrichment Evaluation (F-PROMETHEE), an effective...

The role of carbon dioxide removal (CDR) is undoubtedly crucial in achieving the climate goals and end-of-century global warming target. Given its role as a leader in global climate actions, the European Union (EU) is expected to take a leading role in CDR developments: yet there is a lack of depth in the region's CDR strategy and deployment. A com...

Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immunoinformatic methods have been utilized previously, here for the first time a deep learning framewor...

In this manuscript, a mathematical model known as the Heimburg model is investigated analytically to get the soliton solutions. Both biomembranes and nerves can be studied using this model. The cell membrane’s lipid bilayer is regarded by the model as a substance that experiences phase transitions. It implies that the membrane responds to electrica...

Brain Positron Emission Tomography (PET) imaging has been increasingly important in recent decades for improved detection and staging of brain cancer and other brain illnesses. Many elements, including the choice of radiation detecting medium, contribute to the overall image quality used to characterize a PET system's performance. In our previous s...

Background: In planning radiotherapy treatments, computed tomography (CT) has become a crucial tool. CT scans involve exposure to ionizing radiation, which can increase the risk of cancer and other adverse health effects in patients. Ionizing radiation doses for medical exposure must be kept “As Low As Reasonably Achievable”. Very few articles on g...

This paper mainly addressed the study of the transmission dynamics of infectious diseases and analysed the effect of two different types of viruses simultaneously that cause immunodeficiency in the host. The two infectious diseases that often spread in the populace are HIV and measles. The interaction between measles and HIV can cause severe illnes...

The resilience of a country during the COVID-19 pandemic was determined based in whether it was holistically prepared and responsive. This resilience can only be identified through systematic data collection and analysis. Historical evidence-based response indicators have been proven to mitigate pandemics like COVID-19. However, most databases are...

This paper deals with the soliton solutions for beam movement within a multimode optical fiber featuring a parabolic index shape. It is considered that a Two-Dimensional Nonlinear Schrödinger Equation (2D-NLSE) with an instantaneous Kerr nonlinearity of the kind can represent the beam dynamics. Nonlinear Multimode Optical Fibers (MMFs) of this kind...

Iron oxide nanoparticles (Fe 2 O 3 NPs) were synthesized utilizing Mentha spicata sourced from Cyprus as a stabilizing agent. The study delved into assessing the antimicrobial, cytotoxic, anti-proliferative, and anti-migratory potential of Fe 2 O 3 NPs through disc diffusion, trypan blue, and 3-[4, 5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium br...

The urgent need to mitigate the severe environmental impacts of climate change necessitates a transition to a low-carbon energy infrastructure, crucial for decarbonization and achieving global sustainability goals. This study investigates the decarbonization trajectories of five major economies and significant carbon emitters: the United States of...

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus that caused the outbreak of the coronavirus disease 2019 (COVID-19). The COVID-19 outbreak has led to millions of deaths and economic losses globally. Vaccination is the most practical solution, but finding epitopes (antigenic peptide regions) in the SAR...

Healthcare-associated infections (HAIs) are the most common adverse events in healthcare and constitute a major global public health concern. Surveillance represents the foundation for the effective prevention and control of HAIs, yet conventional surveillance is costly and labor intensive. Artificial intelligence (AI) and machine learning (ML) hav...

BACKGROUND Artificial intelligence (AI) models are being increasingly studied for the detection of variations and pathologies in different imaging modalities. Nasal septal deviation (NSD) is an important anatomical structure with clinical implications. However, AI-based radiographic detection of NSD has not yet been studied. OBJECTIVE This researc...

One of the most challenging and prevalent side effects of LVAD implantation is that of right heart failure (RHF) that may develop afterwards. The purpose of this study is to review and highlight recent advances in the uses of AI in evaluating RHF after LVAD implantation. The available literature was scanned using certain key words (artificial intel...

Malaria continues to be a major barrier to socioeconomic development in Africa, where its death rate is over 90%. The predictive power of many machine learning models—such as multi-linear regression (MLR), artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFISs) and Random Forest classifier—is investigated in this study usi...

The aim of this study is to analyze and investigate the COVID-19 transmission with effect of symptomatic and asymptomatic in the community. Mathematical model is converted into fractional order with the help of fractal fractional definition. The proposed fractional order system is investigated qualitatively as well as quantitatively to identify its...

In this article, we investigate lump-type solutions of the new integrable time-dependent coefficient (2+1)-dimensional Kadomtsev-Petviashvili equation by employing the Hirota bilinear technique and a suitable ansatz. This equation models the propagation of small-amplitude surface waves in large channels or straits with slowly varying width, depth,...

Especially in the last two decades, due to the developments in durable mechanical circulatory support (MCS) technology and applications, left ventricular assist (LVAD) implantation has become used in more fragile end-stage heart failure patients with higher risk. Despite advances in technology and patient care processes, right heart failure remains...