Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - Scopus: 14CoviDetector: A Transfer Learning-Based Semi Supervised Approach to Detect COVID-19 Using CXR Images(Elsevier B.V., 2023-06) Chowdhury, Deepraj; Das, Anik; Dey, Ajoy; Banerjee, Soham; Golec, Muhammed; Kollias, Dimitrios; Arya, Rajesh Chand; Uhlig, SteveCOVID-19 was one of the deadliest and most infectious illnesses of this century. Research has been done to decrease pandemic deaths and slow down its spread. COVID-19 detection investigations have utilised Chest X-ray (CXR) images with deep learning techniques with its sensitivity in identifying pneumonic alterations. However, CXR images are not publicly available due to users’ privacy concerns, resulting in a challenge to train a highly accurate deep learning model from scratch. Therefore, we proposed CoviDetector, a new semi-supervised approach based on transfer learning and clustering, which displays improved performance and requires less training data. CXR images are given as input to this model, and individuals are categorised into three classes: (1) COVID-19 positive; (2) Viral pneumonia; and (3) Normal. The performance of CoviDetector has been evaluated on four different datasets, achieving over 99% accuracy on them. Additionally, we generate heatmaps utilising Grad-CAM and overlay them on the CXR images to present the highlighted areas that were deciding factors in detecting COVID-19. Finally, we developed an Android app to offer a user-friendly interface. We release the code, datasets and results’ scripts of CoviDetector for reproducibility purposes; they are available at: https://github.com/dasanik2001/CoviDetector © 2024 Elsevier B.V., All rights reserved.Article Citation - Scopus: 5Barriers to Strategy Implementation in Turkey’s Healthcare Industry: Hospital Manager Perspectives(Informa UK Ltd, 2021-08-02) Ocak, Saffet; Aladag, Omer Faruk; Köseoglu, Mehmet Ali; King, Brian E.M.Although strategy implementation has profound implications for delivering efficient service, it has been largely neglected in the healthcare management literature. This study explores the barriers to effective implementation of strategic plans in healthcare organizations. To achieve this end, empirical data were collected from 185 hospital managers in Turkey using a survey-based methodology. A descriptive analysis was undertaken of the survey responses to determine the most important barriers to strategy implementation. The most significant barriers undermining strategy implementation efforts were found to be: low employee motivation, an exclusive focus on financial performance and lack of consensus among decision makers. © 2023 Elsevier B.V., All rights reserved.