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    Assessing the conformance of foods in school canteens in terms of health in Malatya a city of Turkey
    (2018) Özer, Ali; Celik Seyitoglu, Duygu; Tekin, Çiğdem; Gokce, Ayse
    Abstract: A healthy diet for students is an important concept in terms of school health. In this regard, selling unhealthy foods in the school canteens causes a serious threat. With this study, we aimed to determine how well the “Turkey Healthy Nutrition and Active Life Program” with the number 2010\22 released by the Prime Minister’s Office was applied at schools, and to reveal how reliable school canteens were in this context. This is a descriptive study. The sample size was calculated as 37 by considering the ‘rate of chips sales in the school canteen as 2.65%’ with a power of 80% and a confidence level of 95%. Stratified sampling method was used to stratify the schools; after which 18 primary schools, 13 secondary schools and 6 high schools were selected. Statistic were expressed in numbers and percentages. It was observed that despite the prohibition, fruit-flavored beverages were sold in 51.4% of the schools included in the study, cokes were sold in 10.8% of the. Moreover, chips and french fries were present in the canteens in 18.9% and 8.1% of the included schools, respectively. Among the foods and drinks recommended in the circular, these school canteens had ayran (89.2%), milk (83.8%), yoghurt (18.9%), fresh fruits (8.1%) and fresh-squeezed fruit–vegetable juices (5.4%). Although the sales of healthy beverages in the school canteens were high, the sales of unhealthy beverages were also high. The sales of yoghurt, fresh fruit and fresh-squeezed fruit–vegetable juices were lower. Moreover, French fries and chips that should not be present in the canteens were also sold, which is thought-provoking.
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    The use of artificial intelligence in different medical branches: An overview of the literature
    (2019) Gunes, Oytun; Gunes, Gulsen; Celik Seyitoglu, Duygu
    Abstract: The goal of this study is to help create a perspective about usage of Artificial Intelligence in some branches of medicine as oncology, radiology, surgery, emergency medicine, etc. A literature review of “Artificial Intelligence in medicine” and for the use of artificial intelligence in some medical branches has been done. Radiology is one of the most notable in the artificial intelligence field and open to many developments in this field. Ten millions of radiology reports and billions of images are now digitally accumulated, simplifying the “big data” concept and creating the bottom line for Artificial Intelligence research. Pathologists used Artificial Intelligence to reduce the error rate of diagnosis of cancer-positive lymph nodes. The accuracy of cancer prediction results has increased considerably in 15-20% of recent years with the application of Machine Learning techniques. Two deep learning systems trained to detect and treat diabetic retinopathy and macular edema achieved high specificities (98%) and sensitivity (87% - 90%) to detect moderate retinopathy and macular edema using a large of retinal photographs in ophthalmology. Several Machine Learning models have promised to develop current triage methods in the Emergency Departments. Surgeons will likely see the Artificial Intelligence analysis of the population and patient-specific data in the future. Artificial Intelligence can certainly help doctors make better clinical decisions and judgments in certain functional areas in health care.