2022 - Cilt 4 - Sayı 1
Bu koleksiyon için kalıcı URI
Güncel Gönderiler
Öğe A new method based CNN combined with genetic algorithm and support vector machine for covid-19 detection by analyzing x-ray images(Altınbaş Üniversitesi, 2022) Dawood, Karam MohammedCOVID-19 is an infectious disease caused by the most recently discovered coronavirus. This new type of virus and disease was unknown before the outbreak began in Wuhan, China in December 2019. COVID-19 poses a serious public health threat. Older adults and people with pre-existing medical conditions such as diabetes, hypertension, heart disease, chronic lung diseases, obesity are at higher risk of experiencing complications and serious illness. The computer scientist applied several machine learning and deep learning techniques to detect COVID-19 in last year. In this study, efficient COVID-19 detection framework presented to detect COVID-19 by analyzing x-ray tests. The proposed framework based CNN combined with genetic algorithm and SVM classifier. The main contribution in this study is combining CNN with genetic algorithm and SVM to detect COVID-19 with accurate estimation and minimum execution time. Several scenarios are executed to validated the presented method. Finally, the obtained results compared with several studies presented to solve this problem.Öğe Detection of covid-19 pneumonia effects in chest x-rays using deep learning(Altınbaş Üniversitesi, 2022) Ahmed, Mohammed KhameesThe development of technological tools based on artificial intelligence (AI) could contribute significantly in the fight against COVID-19. AI is the ability of a machine to apply human cognitive functions. In this paper we propose a deep learning based model for COVID-19 detection relying on the effects it yields on the lungs.Öğe Detection of covid-19 in low energy chest x-rays using fast R-CNN(Altınbaş Üniversitesi, 2022) Mamoori, Maryam Kareem Sakran; Ibrahim, Abdullahi AbduIn recent years, it has been shown that deep learning can produce similar performance increases in the domain of medical image analysis for object detection and segmentation tasks. Notable recent work includes important medical applications, for example, in the field of pulmonology (classification of lung diseases and detection of pulmonary nodules on CT images in this paper, we present a variation of CNNs, which works extremely well on a current data set — a customized architecture with optimal parameters. In our contribution, we focus on lowering the complexity of our network, while yet reaching a phenomenally high degree of accuracy. To achieve this aim, our model has been tailored for high performance and an easy design.Öğe Building an electronic health portal with an e-health application to communicate with patients(Altınbaş Üniversitesi, 2022) Fazea, Ali Al; Ibrahim, Abdullahi AbduPatients have better access to their healthcare records and resources thanks to e-health portals. We create and deploy an e-health portal that efficiently integrates a variety of background medical services. The most difficult aspect of implementing such a system is ensuring that essential security criteria are met, such as patient data confidentiality, diagnostic outcome accuracy, and healthcare service availability. In this study, the design and implementation of a common electronic health records system, which various clinicians and patients can access, is presented depending on the RBAC access control. We focused on creating a patient- specific password through PHP programming functions. It is also possible, on this portal, to establish effective communication between the doctor and the patient, such as booking appointment electronically. Moreover, doctors can use the system to communicate urgent reports regarding the spread of newly discovered pandemics such as Coronavirus. System testing and evaluation are also offered.
