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Recent Submissions

Class distance weighted cross entropy loss for classification of disease severity Polat, Gorkem; Çağlar, Ümit Mert; Temizel, Alptekin (2025-04-01) Assessing disease severity with ordinal classes, where each class reflects increasing severity levels, benefits from loss functions designed for this ordinal structure. Traditional categorical loss functions, like Cross-En...
Presenting predictions and performance of probabilistic models for clinical decision support in trauma care Alptekin, Cansu; Wohlgemut, Jared M.; Perkins, Zane B.; Marsh, William; Tai, Nigel R. M.; Yet, Barbaros (2025-02-01) Introduction: Both predictions and performance of clinical predictive models can be presented with various verbal and visual representations. This study aims to investigate how different risk and performance presentations ...
A Review of LLM Security: Threats and Mitigations Günay, Bengi; Tezcan, Cihangir; Department of Cybersecurity (2025-1-23) Large Language Models (LLMs) are advanced AI systems trained on massive datasets to process and generate natural language. These models can understand, summarize, and create human-like text with remarkable accuracy. Sinc...
JAMMER DETECTION IN AUTONOMOUS VEHICLES WITH MACHINE LEARNING Demiryürek, Mert; Taşkaya Temizel, Tuğba; Department of Information Systems (2025-1-23) Wireless communication systems of autonomous vehicles may be vulnerable to threats such as jammer attacks. As a result of these attacks, operational failures and security problems may occur. This study aims to classify whi...
A Survey on Password-free Authentication Method: Passkey Doğan, Sait Göktuğ; Tezcan, Cihangir; Department of Cybersecurity (2025-1-15) When a need for to authenticate someone or something, the first answer that comes to mind is to use passwords. While implemented and used properly, passwords are more than enough to securely authenticate. But like everythi...
ASSESSING ADVANCED RETRIEVALAUGMENTED GENERATION TECHNIQUES FOR QUESTION ANSWERING: A CASE STUDY ON GOVERNMENTAL SERVICES Alzariqi, Abdullah Talat Ahmed Mohammed; Taşkaya Temizel, Tuğba; Department of Information Systems (2025-1-15) This case study evaluates advanced Retrieval-Augmented Generation (RAG) methods to enhance question answering in conversational AI for government services, focusing on data from the Ministry of Health and Prevention. It as...
Comprehensive whole-genome sequencing reveals origins of mutational signatures associated with aging, mismatch repair deficiency and temozolomide chemotherapy Hwang, Taejoo; Sitko, Lukasz Karol; Khoirunnisa, Ratih; Navarro-Aguad, Fernanda; Samuel, David M.; Park, Hajoong; Cheon, Banyoon; Mutsnaini, Luthfiyyah; Lee, Jaewoong; Otlu Sarıtaş, Burçak; Takeda, Shunichi; Lee, Semin; Ivanov, Dmitri; Gartner, Anton (2025-01-13) In a comprehensive study to decipher the multi-layered response to the chemotherapeutic agent temozolomide (TMZ), we analyzed 427 genomes and determined mutational patterns in a collection of ∼40 isogenic DNA repair-defici...
Security Assessment of the Smartcard Systems at Middle East Technical University akçören, berkay; Tezcan, Cihangir; Department of Cybersecurity (2025-1-10) Smartcards are portable devices that can communicate wirelessly and contain microchips capable of transferring, processing or storing data. They serve practical and reliable solutions for everyday problems such as identifi...
Brain Network Connectivity of the N-Back Task in Schizophrenia Groups According to M1 Receptor Polymorphism Çağlayan, Ece; Çakır, Murat Perit; Kır, Yağmur; Department of Medical Informatics (2025-1-10) This study explores the impact of clozapine, an atypical antipsychotic, on cognitive function and brain connectivity in 43 schizophrenia patients, focusing on the M1 muscarinic receptor and its rs2067477 polymorphism. Buil...
API Security Guideline for Developers and Product Owners Akgündüz, Okan; Tezcan, Cihangir; Department of Cognitive Sciences (2025-1-10) A security guideline with security topics, practices, and recommendations to consider when designing, developing, and maintaining an API service for developers and product owners.
INVESTIGATING THE SEMANTIC SIMILARITY EFFECT ON DELAYED FREE RECALL USING WORD EMBEDDINGS Büyükyaprak, Burak; Yet, Barbaros; Kılıç Özhan, Aslı; Department of Cognitive Sciences (2025-1-10) Episodic memory is a type of long-term memory that encodes and retrieves personal experiences associated with their context. Previous episodic memory studies showed that the context or pre-existing knowledge about retrieve...
FACILITATING COLLABORATIVE DEEPFAKE DETECTION BASED ON BLOCKCHAIN TECHNOLOGY AND REPUTATION Zemin, Mustafa; Baykal, Nazife; Department of Information Systems (2025-1-07) The increasing popularity of deepfake technology is progressively posing a significant threat to information integrity and security. There are numerous solutions to detect deepfakes, but they usually fail to detect all o...
A robust approach for predicting mutation effects on transcription factor binding: insights from mutational signatures in 560 breast cancer samples Kılınç, Hüseyin Hilmi; Otlu Sarıtaş, Burçak; Department of Bioinformatics (2025-1-07) Somatic mutations, particularly in non-coding regions, can perturb transcription factor (TF)-DNA interactions, influencing gene regulatory networks and contributing to cancer development. Thus, they require further compreh...
Cross-Session EEG-Based Mental Workload Classification Using Graph Neural Networks for Reproducible Brain-Computer Interface Applications Demirezen, Güliz; Taşkaya Temizel, Tuğba; Brouwer, Anne-Marie; Department of Information Systems (2024-12-20) Human mental workload refers to the portion of an operator’s cognitive capacity used during a task. Performance of an operator may deteriorate if resource requirements of a task is higher than the available capability. Eff...
Representations in design computing through 3-D deep generative models Çakmak, Başak; Öngün, Cihan (2024-12-10) This paper aims to explore alternative representations of the physical architecture using its real-world sensory data through artificial neural networks (ANNs). In the project developed for this research, a detailed 3-D po...
Using Deep Learning Models for Structural Break Detection in Time Series Yazıcı, Pınar Cemre; Yozgatlıgil, Ceylan; Department of Information Systems (2024-12-06) This study addresses the detection and localization of structural breaks in time series data through a comprehensive pipeline, encompassing synthetic data generation, model training, and validation. Synthetic datasets were...
Secondary data analysis using Evidence-Based Bayesian Networks with an application to investigate the determinants of childhood stunting Yet, Barbaros; Öykü Başerdem, Elif; Rosenstock, Todd (2024-12-05) Secondary data – data previously collected by other researchers for a different purpose – offers a cost-effective and readily available resource for research and policy or program design but presents challenges due to the ...
Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study Aydın Son, Yeşim (2024-12-01) Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our app...
Design, implementation and usability analysis of patient empowerment in ADLIFE project via patient reported outcome measures and shared decision making Erturkmen, Gokce B. Laleci; Juul, Natassia Kamilla; Redondo, Irati Erreguerena; Gil, Ana Ortega; Berastegui, Dolores Verdoy; de Manuel, Esteban; Yuksel, Mustafa; Sarigul, Bunyamin; Yılmaz, Gökçen; Choi Keung, Sarah N. L. I. M.; Arvanitis, Theodoros N.; Syse, Thea Damkjaer; Bloemeke-Cammin, Janika; Kaye, Rachelle; Sorknæs, Anne Dichmann (2024-12-01) Introduction: This paper outlines the design, implementation, and usability study results of the patient empowerment process for chronic disease management, using Patient Reported Outcome Measurements and Shared Decision-M...
Classification of System and Software Related FDA Medical Device Recalls with a Three-Level Taxonomy Approach: Defibrillator Case Önder, Nazire Merve; Özcan Top, Özden (2024-12-01) In the healthcare domain, where safety is paramount, medical device recalls are highly critical events that can pose significant risks to health. The U.S. Food and Drug Administration (FDA) maintains a comprehensive databa...

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