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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.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) .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 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 Citation - WoS: 16Citation - Scopus: 17Subacute Thyroiditis Related To Sars-Cov Vaccine and Covid-19 (thyrovac Study): a Multicenter Nationwide Study(Endocrine Soc, 2023) Batman, Adnan; Yazici, Dilek; Dikbas, Oguz; Agbaht, Kemal; Saygili, Emre Sedar; Demirci, Ibrahim; Sahin, MustafaContext The aims of the study are to compare characteristics of subacute thyroiditis (SAT) related to different etiologies, and to identify predictors of recurrence of SAT and incident hypothyroidism. Methods This nationwide, multicenter, retrospective cohort study included 53 endocrinology centers in Turkey. The study participants were divided into either COVID-19-related SAT (Cov-SAT), SARS-CoV-2 vaccine-related SAT (Vac-SAT), or control SAT (Cont-SAT) groups. Results Of the 811 patients, 258 (31.8%) were included in the Vac-SAT group, 98 (12.1%) in the Cov-SAT group, and 455 (56.1%) in the Cont-SAT group. No difference was found between the groups with regard to laboratory and imaging findings. SAT etiology was not an independent predictor of recurrence or hypothyroidism. In the entire cohort, steroid therapy requirement and younger age were statistically significant predictors for SAT recurrence. C-reactive protein measured during SAT onset, female sex, absence of antithyroid peroxidase (TPO) positivity, and absence of steroid therapy were statistically significant predictors of incident (early) hypothyroidism, irrespective of SAT etiology. On the other hand, probable predictors of established hypothyroidism differed from that of incident hypothyroidism. Conclusion Since there is no difference in terms of follow-up parameters and outcomes, COVID-19- and SARS-CoV-2 vaccine-related SAT can be treated and followed up like classic SATs. Recurrence was determined by younger age and steroid therapy requirement. Steroid therapy independently predicts incident hypothyroidism that may sometimes be transient in overall SAT and is also associated with a lower risk of established hypothyroidism.Article Citation - WoS: 16Pulmonary Rehabilitation Principles in Sars-Cov Infection (covid-19): the Revised Guideline for the Acute, Subacute, and Post-Covid Rehabilitation(Baycinar Medical Publ-baycinar Tibbi Yayincilik, 2021) Aytur, Yesim Kurtais; Koseoglu, Belma Fusun; Taskiran, Ozden Ozyemisci; Ordu-Gokkaya, Nilufer Kutay; Delialioglu, Sibel Unsal; Tur, Birkan Sonel; Tikiz, CananCoronavirus 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.Article Citation - WoS: 170Mortality Analysis of Covid-19 Infection in Chronic Kidney Disease, Haemodialysis and Renal Transplant Patients Compared With Patients Without Kidney Disease: a Nationwide Analysis From Turkey(Oxford Univ Press, 2020) Ozturk, Savas; Turgutalp, Kenan; Arici, Mustafa; Odabas, Ali Riza; Altiparmak, Mehmet Riza; Aydin, Zeki; Ates, KenanBackground. Chronic kidney disease (CKD) and immunosuppression, such as in renal transplantation (RT), stand as one of the established potential risk factors for severe coronavirus disease 2019 (COVID-19). Case morbidity and mortality rates for any type of infection have always been much higher in CKD, haemodialysis (HD) and RT patients than in the general population. A large study comparing COVID-19 outcome in moderate to advanced CKD (Stages 3-5), HD and RT patients with a control group of patients is still lacking. Methods. We conducted a multicentre, retrospective, observational study, involving hospitalized adult patients with COVID-19 from 47 centres in Turkey. Patients with CKD Stages 3-5, chronic HD and RT were compared with patients who had COVID-19 but no kidney disease. Demographics, comorbidities, medications, laboratory tests, COVID-19 treatments and outcome [in-hospital mortality and combined in-hospital outcome mortality or admission to the intensive care unit (ICU)] were compared. Results. A total of 1210 patients were included [median age, 61 (quartile 1-quartile 3 48-71) years, female 551 (45.5%)] composed of four groups: control (n = 450), HD (n = 390), RT (n = 81) and CKD (n = 289). The ICU admission rate was 266/1210 (22.0%). A total of 172/1210 (14.2%) patients died. The ICU admission and in-hospital mortality rates in the CKD group [114/289 (39.4%); 95% confidence interval (CI) 33.9-45.2; and 82/289 (28.4%); 95% CI 23.9-34.5)] were significantly higher than the other groups: HD = 99/390 (25.4%; 95% CI 21.3-29.9; P < 0.001) and 63/390 (16.2%; 95% CI 13.0-20.4; P < 0.001); RT = 17/81 (21.0%; 95% CI 13.2-30.8; P = 0.002) and 9/81 (11.1%; 95% CI 5.7-19.5; P = 0.001); and control = 36/450 (8.0%; 95% CI 5.8-10.8; P < 0.001) and 18/450 (4%; 95% CI 2.5-6.2; P < 0.001). Adjusted mortality and adjusted combined outcomes in CKD group and HD groups were significantly higher than the control group [hazard ratio (HR) (95% CI) CKD: 2.88 (1.52-5.44); P = 0.001; 2.44 (1.35-4.40); P = 0.003; HD: 2.32 (1.21-4.46); P = 0.011; 2.25 (1.23-4.12); P = 0.008), respectively], but these were not significantly different in the RT from in the control group [HR (95% CI) 1.89 (0.76-4.72); P = 0.169; 1.87 (0.81-4.28); P = 0.138, respectively]. Conclusions. Hospitalized COVID-19 patients with CKDs, including Stages 3-5 CKD, HD and RT, have significantly higher mortality than patients without kidney disease. Stages 3-5 CKD patients have an in-hospital mortality rate as much as HD patients, which may be in part because of similar age and comorbidity burden. We were unable to assess if RT patients were or were not at increased risk for in-hospital mortality because of the relatively small sample size of the RT patients in this study.Editorial Citation - Scopus: 1Safety and Feasibility of Surgery for Oropharyngeal Cancers During the Sars-Cov(Frontiers Media Sa, 2021) Gorphe, Philippe; Grandbastien, Bruno; Dietz, Andreas; Duvvuri, Umamaheswar; Ferris, Robert L.; Golusinski, Wojciech; Simon, Christian[No Abstract Available]Article Citation - WoS: 6Citation - Scopus: 8Food Safety Awareness, Changes in Food Purchasing Behaviour and Attitudes Towards Food Waste During Covid-19 in Türkiye(Mdpi, 2023) Erol, Irfan; Mutus, Begum; Ayaz, Naim Deniz; Stowell, Julian D.; Siriken, Belgin(1) Background: The COVID-19 pandemic brought the key issues of food security, food safety, and food waste into sharp focus. Turkiye is in the enviable position of being among the top ten agricultural economies worldwide, with a wide diversity of food production. This survey was undertaken in order to gain insights into consumer behaviour and attitudes in Turkiye with respect to these issues. The objective was to highlight strengths and weaknesses, identify areas for improvement, and present strategies for the future. (2) Methods: This survey was carried out between April and May 2022 in 12 provinces throughout Turkiye. Face-to-face interviews were performed with 2400 participants representing a cross-section of ages, educational attainment, and socio-economic categories. The findings were evaluated statistically. (3) Results: The results provide an insight into attitudes and behaviours, both pre-COVID-19 and during the pandemic. In several ways, the pandemic enhanced knowledge and improved behaviour, leading to improvements in diet and reductions in food waste. However, worrying concerns about food safety persist. Specific attention has been given to understanding patterns of bread consumption, particularly in consideration of waste. (4) Conclusions: It is hoped that the results of this survey will increase dialogue between the components of the food sector, encourage education initiatives, and contribute to improving food safety and security and reducing food waste in Turkiye and beyond.
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