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Article Citation - WoS: 21Citation - Scopus: 35Deep Learning-Based Computer-Aided Diagnosis (cad): Applications for Medical Image Datasets(Mdpi, 2022) Kadhim, Yezi Ali; Khan, Muhammad Umer; Mishra, AlokComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the best optimal features while reducing the amount of data. Lastly, diagnosis prediction (classification) is achieved using learnable classifiers. The novel framework for the extraction and selection of features is based on deep learning, auto-encoder, and ACO. The performance of the proposed approach is evaluated using two medical image datasets: chest X-ray (CXR) and magnetic resonance imaging (MRI) for the prediction of the existence of COVID-19 and brain tumors. Accuracy is used as the main measure to compare the performance of the proposed approach with existing state-of-the-art methods. The proposed system achieves an average accuracy of 99.61% and 99.18%, outperforming all other methods in diagnosing the presence of COVID-19 and brain tumors, respectively. Based on the achieved results, it can be claimed that physicians or radiologists can confidently utilize the proposed approach for diagnosing COVID-19 patients and patients with specific brain tumors.Book Part Citation - Scopus: 2Molecular Mimicry Study Between Peptides of SARS-CoV-2 and Neutrophil Extracellular Traps-Related Proteins(Elsevier, 2024) Adiguzel,Y.; Shoenfeld,Y.Background Neutrophil extracellular traps (NETs) are observed in both COVID-19 pathology and autoimmune disorders, and molecular mimicry is a mechanism that can lead to an autoimmune response. Methods Similar sequences between SARS-CoV-2 proteins and 5 proteins (plasminogen receptor KT: PLRKT, myeloperoxidase: MPO, proteinase 3: PR-3, neutrophil elastase: NE, matrix metalloproteinase 9: MMP-9) that are present in NETs were searched. Human and SARS-CoV-2 sequence pairs were identified. Those among the identified sequence pairs, which are predicted as strong-binding peptides or epitopes of the same selected MHC class I and class II alleles, were predicted. Results In the case of MHC class I alleles, similar PLRKT and SARS-CoV-2 peptide sequences with high predicted-affinities to HLA-A*24:02, HLA-B*08:01, and HLA-B*15:01; similar MPO and SARS-CoV-2 peptide sequences with strong predicted-affinities to HLA-A*01:01, HLA-A*26:01, and HLA-B*15:01; and similar MMP-9 and SARS-CoV-2 peptide sequences with elevated predicted-affinities to HLA-B*39:01 were predicted. In the case of MHC class II alleles, similar PLRKT and SARS-CoV-2 peptide sequences with high predicted-affinities to HLA-DPA1*02:01/DPB1*01:01 were predicted. Conclusion This work is a proof-of-concept study, which revealed the potential involvement of molecular mimicry in NET pathology within susceptible individuals, in the case of being infected with SARS-CoV-2, leading to autoimmunity. © 2024 Elsevier B.V. All rights reserved.Review Citation - WoS: 7Citation - Scopus: 9A Survey of Covid-19 Diagnosis Using Routine Blood Tests With the Aid of Artificial Intelligence Techniques(Mdpi, 2023) Habashi, Soheila Abbasi; Koyuncu, Murat; Alizadehsani, RoohallahSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), causing a disease called COVID-19, is a class of acute respiratory syndrome that has considerably affected the global economy and healthcare system. This virus is diagnosed using a traditional technique known as the Reverse Transcription Polymerase Chain Reaction (RT-PCR) test. However, RT-PCR customarily outputs a lot of false-negative and incorrect results. Current works indicate that COVID-19 can also be diagnosed using imaging resolutions, including CT scans, X-rays, and blood tests. Nevertheless, X-rays and CT scans cannot always be used for patient screening because of high costs, radiation doses, and an insufficient number of devices. Therefore, there is a requirement for a less expensive and faster diagnostic model to recognize the positive and negative cases of COVID-19. Blood tests are easily performed and cost less than RT-PCR and imaging tests. Since biochemical parameters in routine blood tests vary during the COVID-19 infection, they may supply physicians with exact information about the diagnosis of COVID-19. This study reviewed some newly emerging artificial intelligence (AI)-based methods to diagnose COVID-19 using routine blood tests. We gathered information about research resources and inspected 92 articles that were carefully chosen from a variety of publishers, such as IEEE, Springer, Elsevier, and MDPI. Then, these 92 studies are classified into two tables which contain articles that use machine Learning and deep Learning models to diagnose COVID-19 while using routine blood test datasets. In these studies, for diagnosing COVID-19, Random Forest and logistic regression are the most widely used machine learning methods and the most widely used performance metrics are accuracy, sensitivity, specificity, and AUC. Finally, we conclude by discussing and analyzing these studies which use machine learning and deep learning models and routine blood test datasets for COVID-19 detection. This survey can be the starting point for a novice-/beginner-level researcher to perform on COVID-19 classification.Article Citation - Scopus: 18Pulmonary rehabilitation principles in SARS-COV-2 infection (COVID-19): The revised guideline for the acute, subacute, and post-COVID-19 rehabilitation(Turkish Society of Physical Medicine and Rehabilitation, 2021) Aytür,Y.K.; Köseoglu,B.F.; Taşkıran,Ö.Ö.; Gökkaya,N.K.O.; Delialioğlu,S.Ü.; Tur,B.S.; Tıkız,C.Coronavirus disease 2019 (COVID-19) is a contagious infection disease, which may cause respiratory, physical, psychological, and generalized systemic dysfunction. The severity of disease ranges from an asymptomatic infection or mild illness to mild or severe pneumonia with respiratory failure and/or death. COVID-19 dramatically affects the pulmonary system. This clinical practice guideline includes pulmonary rehabilitation (PR) recommendations for adult COVID-19 patients and has been developed in the light of the guidelines on the diagnosis and treatment of COVID-19 provided by the World Health Organization and Republic of Turkey, Ministry of Health, recently published scientific literature, and PR recommendations for COVID-19 regarding basic principles of PR. This national guideline provides suggestions regarding the PR methods during the clinical stages of COVID-19 and post-COVID-19 with its possible benefits, contraindications, and disadvantages. © 2021 All right reserved by the Turkish Society of Physical Medicine and RehabilitationArticle Citation - WoS: 3Citation - Scopus: 3The Role of Honor Concerns in Disclosing (vs. Hiding) COVID-19 Diagnosis: Insights from Turkiye(Springer/plenum Publishers, 2023) Ceylan-Batur, Suzan; Dogulu, Canay; Akbas, Gulcin; Yet, Barbaros; Uskul, Ayse K. K.Members of honor cultures value engaging in moral behaviors and managing their social image to maintain their honor. These two goals reflect reputation and integrity concerns, which also have bearing on gender roles. In the current study, we examined a) evaluations of women and men described as diagnosed with COVID-19 and as either hiding or disclosing their diagnosis, b) the moderating role of honor concerns (reputation and integrity) and the gender of the infected person in these evaluations, and c) the relationship between honor concerns and individuals' own disclosure preferences among participants living in Turkiye, a country that exemplifies an honor culture. Findings revealed that participants with stronger reputation concerns evaluated a woman's hiding behavior more favorably than that of a man's. Moreover, higher integrity concerns were associated with lower levels of participants' own preference to hide a diagnosis for both men and women, whereas reputation concerns were positively associated with a preference for hiding a diagnosis among men only. Furthermore, a content analysis of participants' open-ended explanations of their views on women's and men's motivation to hide a diagnosis revealed further evidence for the gendered nature of reputation concerns. Our findings point to the importance of prioritizing integrity concerns (and downplaying reputation concerns) in public health campaigns in honor cultures.Article Citation - WoS: 5Citation - Scopus: 8A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification(Mdpi, 2024) Kadhim, Yezi Ali; Guzel, Mehmet Serdar; Mishra, AlokMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep learning techniques, which were based on a convolutional neural network (CNN) or autoencoder, to extract features and combine them with the next step of the meta-heuristic algorithm in order to select optimal features using the particle swarm optimization (PSO) algorithm. This combination sought to reduce the dimensionality of the datasets while maintaining the original performance of the data. This is considered an innovative method and ensures highly accurate classification results across various medical datasets. Several classifiers were employed to predict the diseases. The COVID-19 dataset found that the highest accuracy was 99.76% using the combination of CNN-PSO-SVM. In comparison, the brain tumor dataset obtained 99.51% accuracy, the highest accuracy derived using the combination method of autoencoder-PSO-KNN.Article Investigation of Sars-Cov Antibody Levels After Covid-19 Vaccine in Chronic Hepatitis B Patients(Aepress Sro, 2024) Kinikli, Sami; Afsar, Fatma Elcin; Dursun, Ali Dogan; Aksoy, Altan; Karahan, Gizem; Cesur, Salih; Urtimur, UfukAIM: The aim was to compare SARS-CoV-2 IgG antibody levels in chronic hepatitis B patients and healthcare personnel selected as the control group and to determine factors such as age, gender, vaccine type, and number of vaccines that may affect the antibody levels. MATERIALS AND METHODS: 87 chronic hepatitis B (CHB) patients followed in Ankara Training and Research Hospital Infectious Diseases Clinic and Mamak State Hospital Infectious Diseases outpatient clinic and 89 healthcare personnel selected as the control group were included in the study. SARS-CoV-2 IgG antibody levels in the serum samples of patients and healthcare personnel who received the COVID-19 vaccine were studied with the ELISA method in the Microbiology Laboratory of Ankara Training and Research Hospital, using a commercial ELISA kit (Abbott, USA) in line with the recommendations of the manufacturer. In the study, SARS-CoV-2 IgG levels were compared in CHB patients and healthcare personnel. In addition, the relationship between SARS-CoV-2 antibody level, gender, average age, natural history of the disease, number of vaccinations, vaccine type (Coronavac TM vaccine alone, BNT162b2 vaccine alone or Coronavac TM and BNT162b2 vaccine (heterologous vaccination)), treatment duration of CHB was investigated. Statistical analyses were made in the SPSS program. A value of p <= 0.05 was considered statistically significant. FINDINGS: A total of 167 people, including 87 CKD patients and 80 healthcare personnel as the control group, were included in the study. SARS-CoV-2 IgG antibody levels were detected above the cut-off level in the entire study group, regardless of the vaccine type. No difference was detected in SARS-CoV-2 IgG titers after COVID-19 vaccination between CHB patients and healthcare personnel. There was a statistically significant difference in SARS-CoV-2 IgG antibody levels among individuals participating in the study according to vaccine types. Compared to those who received Coronavac TM vaccine alone, the average SARS-CoV-2 IgG level was found to be statistically significantly higher in those who received BNT162b2 vaccine alone or heterologous vaccination with Coronavac TM + BNT162b2 vaccine. There was no difference between the groups in terms of age, gender, number of vaccinations, natural transmission of the disease, and duration of antiviral therapy in the CHD patient group. CONCLUSION: As a result, SARS-CoV-2 IgG antibody levels above the cut-off value were achieved with Coronavac TM and BNT162b2 vaccines in both CHD patients and healthy control groups. however, both CHD patients and healthcare personnel had higher antibody levels than those who received BNT162b2 alone or those who received heterologous vaccination had higher antibody levels than those with Coronavac TM alone. Therefore, if there are no contraindications, BNT162b2 vaccine may be preferred in CHB and health personnel (Tab. 2, Ref. 14) .Article Health Capital and a Sustainable Economic-Growth Nexus: a High-Frequency Analysis During Covid-19(Mdpi, 2024) Sungur, Nazli Ceylan; Akdogan, Ece C.; Gokten, SonerThe recent COVID-19 pandemic effectively concretized the vitality of health expenditure and the economic-growth nexus, and the threat of new pandemics make re-examining this relationship a necessity. Consequently, this paper focuses on this nexus for developed OECD countries, paying particular attention to the effects of the COVID-19 pandemic. The use of stock indices as proxy variables for health expenditure and economic growth enabled the examination of this nexus by using high-frequency data and financial econometric techniques, specifically via rolling correlation and bivariate GARCH analyses. The data span 1170 observations between 15 May 2018 and 11 November 2022. Since the research period overlaps with the outbreak of Ukraine-Russia war, additional insights are obtained regarding the effects of the war as well. It was found that an increase in health expenditure leads to a delayed increase in economic growth even in the short term, and this relationship mainly develops during crises such as epidemics, wars, supply chain breakdowns, etc., for developed OECD countries. Given the aging population of developed countries, which will probably deteriorate the health status of those countries in the near future, the increasing political tensions around the globe and the considerations of a global recession highlight the importance and the inevitability of investments in health capital for developed countries as well.Article Breast Cancer Management During the Covid Pandemic(Coll Physicians & Surgeons Pakistan, 2024) Sariyildiz, Gulcin Turkmen; Ayhan, Fikriye FigenObjective: To explore the impact of COVID-19 among both the newly diagnosed patients and patients under follow-up for breast cancer by focusing on patients' accessibility to management and comparing the distribution of them before and during pandemic. Study Design: Single -centric retrospective study. Place and Duration of the Study: Department of General Surgery and Department of Physical Medicine and Rehabilitation, Atilim University, Medicana International Ankara Hospital, Ankara, Turkiye, from March 2018 to 2022. Methodology: The data were collected to analyse numbers and distributions of physician visits regarding breast cancer. Results: The mean age of patients was 55.98 +/- 12.60 years. The percentages of newly diagnosed cases showed similarity (7.37% vs. 9.79%) before and during the pandemic (p = 0.18). The number of imaging studies decreased by 53.33% in patients under follow-up (p = 0.006), despite screening tests showed a similar trend (p = 0.145). General surgery visits marked up (+44.6%), in contrast to plastic surgery visits (-42.04%, p <0.001). Patients' admissions decreased in many COVID-19 related clinics (pulmonology, emergency, internal medicine, and intensive care), but cardiology (+96.59%) and rehabilitation (+75%) admissions increased during the pandemic (p <0.001). The number of medical oncology and radiation oncology visits did not change (p >0.05). Conclusion: Total number of physician visits was similar before and during the pandemic despite the changing distribution. While COVID-19 led to markedly rising trends of surgical, cardiological, and rehabilitative management in patients with breast cancer, falling trends were seen in other specialities except oncology which showed a plateau during two years. The falling trends of visits to pulmonology, emergency, internal medicine, and intensive care clinics may be explained by crowded COVID-19 cases.Article Reinterpreting Architectural Precedents: the Enduring Relevance and Transformative Capacity of Villa Savoye’s Design Principles(Istanbul Teknik Universitesi, Faculty of Architecture, 2025) Cinar, SinemThis paper examines the evolving role of architectural precedents, focusing on Le Corbusier’s Villa Savoye, and emphasizes their continued relevance and transformative capacity within architectural design culture. It illustrates how engagement with precedents influences their reinterpretation and adaptation in changing contexts. Villa Savoye, a defining example of Modern Architecture, gained renewed attention during the COVID-19 pandemic, particularly through its freestanding washbasin at the entrance. This feature suggested a transitional, hygienic space addressing emerging concerns about sanitization upon returning home. Such recognition highlights how precedents can acquire new meaning when viewed through altered perspectives. Building on the idea that precedents like Villa Savoye offer fresh insights as inquiries evolve, this paper extends discourse on precedent and design. It explores the project’s continued relevance to contemporary architecture, emphasizing adaptability of its design principles. The study assesses the lasting impact of these principles—pilotis, open plan, roof garden, horizontal windows, free façade, and architectural promenade— on both Le Corbusier’s later works and contemporary practices. Through an interpretive-historical methodology, the research integrates primary sources and theoretical critiques to illustrate how evolving perspectives shape the relationship between precedent and design. Comparative analyses examine reinterpretations of these principles in Le Corbusier’s later works and contemporary architecture. Ultimately, this study contributes to architectural literature by framing precedents as dynamic resources that facilitate meaningful dialogue between past and present. It emphasizes their capacity to revitalize architectural culture, generating continuous insights in response to evolving challenges. © 2025, Istanbul Teknik Universitesi, Faculty of Architecture. All rights reserved.
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