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Conference Object ANALYSIS OF NEUROONCOLOGICAL DATA TO PREDICT SUCCESS OF OPERATION THROUGH CLASSIFICATION(Assoc Computing Machinery, 2016) Bagherzadi, Negin; Borcek, Alp Ozgun; Tokdemir, Gul; Cagiltay, Nergiz; Maras, H. HakanData mining algorithms have been applied in various fields of medicine to get insights about diagnosis and treatment of certain diseases. This gives rise to more research on personalized medicine as patient data can be utilized to predict outcomes of certain treatment procedures. Accordingly, this study aims to create a model to provide decision support for surgeons in Neurooncology surgery. For this purpose, we have analyzed clinical pathology records of Neurooncology patients through various classification algorithms, namely Support Vector Machine, Multi Perceptron and Naive Bayes methods, and compared their performances with the aim of predicting surgery complication. A large number of factors have been considered to classify and predict percentage of patient's complication in surgery. Some of the factors found to be predictive were age, sex, clinical presentation, previous surgery type etc. For classification models built up using Support Vector Machine, Naive Bayes and Multi Perceptron, Classification trials for Support Vector Machine have shown %77.47 generalization accuracy, which was established by 5-fold cross-validation.Article A User Task Design Notation for Improved Software Design(Peerj inc, 2021) Ozcan, Eda; Topalli, Damla; Tokdemir, Gul; Cagiltay, Nergiz ErcilSystem design is recognized as one of the most critical components of a software system that bridges system requirements and coding. System design also has a significant impact on testing and maintenance activities, and on further improvements during the lifespan of the software system. Software design should reflect all necessary components of the requirements in a clear and understandable manner by all stakeholders of the software system. To distinguish system elements, separation of concerns in software design is suggested. In this respect, identification of the user tasks, i.e., the tasks that need to be performed by the user, is not currently reflected explicitly in system design documents. Our main assumption in this study is that software quality can be improved significantly by clearly identifying the user tasks from those that need to be performed by the computer system itself. Additionally, what we propose has the potential to better reflect the user requirements and main objectives of the system on the software design and thereby to improve software quality. The main aim of this study is to introduce a novel notation for software developers in the frame of UML Activity Diagram (UML-AD) that enables designers to identify the user tasks and define them separately from the system tasks. For this purpose, an extension of UML-AD, named UML-ADE (UML-Activity Diagram Extended) was proposed. Afterwards, it was implemented in a serious game case for which the specification of user tasks is extremely important. Finally, its effectiveness was analyzed and compared to UML-AD experimentally with 72 participants. The defect detection performance of the participants on both diagrams with two real-life serious game scenarios was evaluated. Results show a higher level of understandability for those using UML-ADE, which in turn may indicate a better design and higher software quality. The results encourage researchers to develop specific design representations dedicated to task design to improve system quality and to conduct further evaluations of the impact of these design on each of the above mentioned potential benefits for the software systems.Conference Object Citation - WoS: 1Patient Safety & Clinical Decision Support Systems (cdss): a Case Study in Turkey(Ieee, 2015) Menekse, Gonca Gokce; Cagiltay, Nergiz Ercil; Tokdemir, GulDecision making process is crucial in several stages of clinical procedures. On the other hand, there are not many studies showing the implications of decision support systems in clinical environments. Hence, adaptation of Decision Support Systems to clinical environment is getting more important as we can collect more data through sensors and yet cannot use it effectively in decision making process. This study aims to understand the effects, benefits and obstacles utilizing CDSS in healthcare. For this purpose, 60 CDSS studies were analyzed to better understand their purpose, implementation domain, and success degrees in the world. Also, a case study was made for analyzing the situation in Turkey. The results show that in the field of neurosurgery, the level of analysis of neurosurgical data in Turkey is very low. The results show an urgent need for collaboration of IT experts and medical authorities to better record and analyze clinical data in the field of neurosurgery.Article Citation - WoS: 22Citation - Scopus: 37Performing and Analyzing Non-Formal Inspections of Entity Relationship Diagram (erd)(Elsevier Science inc, 2013) Cagiltay, Nergiz Ercil; Tokdemir, Gul; Kilic, Ozkan; Topalli, DamlaDesigning and understanding of diagrammatic representations is a critical issue for the success of software projects because diagrams in this field provide a collection of related information with various perceptual signs and they help software engineers to understand operational systems at different levels of information system development process. Entity relationship diagram (ERD) is one of the main diagrammatic representations of a conceptual data model that reflects users' data requirements in a database system. In today's business environment, the business model is in a constant change which creates highly dynamic data requirements which also requires additional processes like modifications of ERD. However, in the literature there are not many measures to better understand the behaviors of software engineers during designing and understanding these representations. Hence, the main motivation of this study is to develop measures to better understand performance of software engineers during their understanding process of ERD. Accordingly, this study proposes two measures for ERD defect detection process. The defect detection difficulty level (DF) measures how difficult a defect to be detected according to the other defects for a group of software engineers. Defect detection performance (PP) measure is also proposed to understand the performance of a software engineer during the defect detection process. The results of this study are validated through the eye tracker data collected during the defect detection process of participants. Additionally, a relationship between the defect detection performance (PP) of a software engineer and his/her search patterns within an ERD is analyzed. Second experiment with five participants is also conducted to show the correlation between the proposed metric results and eye tracker data. The results of experiment-2 also found to be similar for DF and PP values. The results of this study are expected to provide insights to the researchers, software companies, and to the educators to improve ERD reasoning process. Through these measures several design guidelines can be developed for better graphical representations and modeling of the information which would improve quality of these diagrams. Moreover, some reviewing instructions can be developed for the software engineers to improve their reviewing process in ERD. These guidelines in turn will provide some tools for the educators to improve design and review skills of future software engineers. (c) 2013 Elsevier Inc. All rights reserved.Article Citation - WoS: 2Citation - Scopus: 3Investigating the Relationship Between Sloc and Logical Database Measures To Improve the Early Estimation of Software Cost(World Scientific Publ Co Pte Ltd, 2019) Tokdemir, Gul; Cagiltay, Nergiz ErcilProject planning is a critical activity in the software development life cycle. At the early stages of a project, the managers need to estimate required time, effort and cost to plan, track and then to deliver the project successfully. Many studies have attempted to provide methods for precise software cost estimation. The current software cost estimation methods are mainly based on software size estimation and functional system requirements. The main assumption of this study is that, as the primary source of complexity in today's software is the interaction between the database and the user, database measures may provide inputs allowing current software estimation methods to achieve more accurate results. Accordingly, this study attempts to gain insights from objective measures, collected through the logical database model of software systems, for better prediction of the software's effort and hence cost through software lines of code (SLOC) measure. For this purpose, more than 2.5 million lines of code developed by four different companies, for 79 different software packages with their related database design measures, are analyzed. The results of this study show that there is a close correlation between the software size and database design measure, namely, the number of tables which can be collected at the logical database design stage. By adapting this result, the current estimation models could be improved significantly.
