درخت حوزه‌های تخصصی

Purpose: The Purpose of this paper is to explain the nature and process of digital transformation.Methodology: Its methodology is based on a structured literature review (SLR) and searching scientific sites and specialized resources. One roadmap model, six maturity assessment models, three digital business model transformation approaches and eight digital transformation frameworks are explained interpretively.Findings: Digital transformation is  a strategy and an operating model change, in which technological advancements are leveraged to improve human experiences and operating efficiencies and to evolve the products and services to which customers will remain loyal. A review of research in this field shows that the nature of digital transformation depends on knowledge and knowledge is formed as a valuable asset in people's minds. Therefore, the role of human resources in creating and achieving the transformation is important and fundamental. Findings show that no digital transformation is only technological, it is organizational and requires its own planning, resources and rules. It is clear that we need a model in this kind of transformation journey. Staff capital and its empowerment by knowledge and fundamental requirements are important for success in the digital transformation program. Transformation in culture, in structure, in processes and methods, along with the benefits of the frontier technologies, will lead to a dramatic transformation in the field of business. The environment of organizations is changing faster and has become more volatile, uncertain and complex than in the past. Rapid changes in competition, demand, technology and regulations make it more important than ever for organizations to be able to respond and adapt to their environment. In this context, the pressure on firms to align their business strategy with the technological changes in the environment has significantly increased with the emergence and growing importance of new digital technologies, such as Social Media, Cloud Computing, Big Data and Analytics, Embedded Devices, 3D-Printing, the Internet of Things and Artificial Intelligence. They are profoundly transforming the strategic context of organizations: changing the structure of competition, the behavior and expectations of customers, the way business is conducted, the way products are manufactured and services are delivered, the way of working and, ultimately, entire industries. The growth of technology, in addition to transforming organizational boundaries, has also improved knowledge sharing. As the results indicate, the digital age refers to a time in history when the use of digital technology was generalized throughout the world. We are on the verge of a technological revolution that will fundamentally change the way we live, work and communicate with each other. In terms of scale, scope, and complexity, this transformation will be different from what mankind has already experienced.Conclusion: Digital transformation has affected the work processes of individuals in organizational environments. New methods in combining digital innovations and intensifying inter-organizational collaboration are among the key features of success. Because the goal of digital transformation is a business transformation, it requires different organizational elements, which are explained in the frameworks, to work together like a piece of music in a concert with different instruments played harmoniously and simultaneously

The continuing outbreak of COVID-19 pneumonia is globally concerning. Timely detection of infection ensures prompt quarantine of patient which is crucial for preventing the rapid spread of this contagious disease and also supports the patient with necessary medication. Due to the high infection rate of COVID-19, our health management system needs an automatic diagnosis tool that equips the health workers to pay immediate attention to the needy person. Chest CT is an essential imaging technique for diagnosis and staging of 2019 novel coronavirus disease (COVID-19). The identification of COVID-19 CT findings assists health workers on further clinical evaluation, especially when the findings on CT scans are trivial, the person may be recommended for Reverse-transcription polymerase chain reaction (RT-PCR) tests. Literature reported that the ground-glass opacity (GGO) with or without consolidation are dominant CT findings in COVID-19 patients. In this paper, the U-Net based segmentation approach is proposed to automatically segment and analyze the GGO and consolidation findings in the chest CT scan. The performance of this system is evaluated by comparing the auto-segmented infection regions with the manually-outlines ones on 100 axial chests CT scans of around 40 COVID-19 patients from SIRM dataset. The proposed U-Net with pre-process approach yields specificity of 0.91 ± 0.09 and sensitivity of 0.87 ± 0.07 on segmenting GGO region and specificity of 0.81 ± 0.13 and sensitivity of 0.44 ± 0.17 on segmenting consolidation region. Also the experimental results confirmed that the automatic detection method identifies the CT finding with a precise opacification percentage from the chest CT image.