Artificial intelligence in the healthcare sector: comparison of deep learning networks using chest X-ray images.

Purpose: Artificial intelligence has led to significant developments in the healthcare sector, as in other sectors and fields. In light of its significance, the present study delves into exploring deep learning, a branch of artificial intelligence. Methods: In the study, deep learning networks ResNet101, AlexNet, GoogLeNet, and Xception were considered, and it was aimed to determine the success of these networks in disease diagnosis. For this purpose, a dataset of 1,680 chest X-ray images was utilized, consisting of cases of COVID-19, viral pneumonia, and individuals without these diseases. These images were obtained by employing a rotation method to generate replicated data, wherein a split of 70 and 30% was adopted for training and validation, respectively. Results: The analysis findings revealed that the deep learning networks were successful in classifying COVID-19, Viral Pneumonia, and Normal (disease-free) images. Moreover, an examination of the success levels revealed that the ResNet101 deep learning network was more successful than the others with a 96.32% success rate. Conclusion: In the study, it was seen that deep learning can be used in disease diagnosis and can help experts in the relevant field, ultimately contributing to healthcare organizations and the practices of country managers.

The Mediating Role of Innovative Behavior on the Effect of Digital Leadership on Intrapreneurship Intention and Job Performance.

Depending on technological developments, digital transformation represents an inevitable reality for organizations. Based on this reality, digital leadership, which is a new understanding of leadership, has emerged. In accordance with the literature, digital leaders are expected to transform organizations under the leadership of innovation, thus encouraging high performance and efficiency. The present study aimed to measure the mediating effect of innovative behavior on the effect of digital leadership on job performance and intrapreneurship intention using data collected from 390 people working in the IT sector in Istanbul and a structural equation modeling method. The data obtained in this structural equation modeling study were analyzed in the Smart-PLS program. It is anticipated that the present study, in which the relationship between the variables is supported by various theories, will contribute to the extant literature. The results of this study indicate that innovative behavior has a fully mediating impact on the effect of digital leadership on intrapreneurship intention. Furthermore, it is observed that innovative behavior has a partially mediating impact on the effect of digital leadership on job performance. Considering the results, this study proves that digital leaders need to adopt innovative behavior so as to ensure performance and intrapreneurship in an organization.