Ferda Nur Alpaslan

E-mail

ferda@metu.edu.tr

Department

Department of Computer Engineering

ORCID

0000-0002-9806-1543

Scopus Author ID

6701519251

Web of Science Researcher ID

ABA-4259-2020

Privacy-Preserving Clinical Decision Support for Emergency Triage Using LLMs: System Architecture and Real-World Evaluation Karamanlıoğlu, Alper; Demirel, Berkan; Tural, Onur; Doğan, Osman Tufan; Alpaslan, Ferda Nur (2025-08-01) This study presents a next-generation clinical decision-support architecture for Clinical Decision Support Systems (CDSS) focused on emergency triage. By integrating Large Language Models (LLMs), Federated Learning (FL), a...
Risk Management Based on Machine Learning Tekinbaş, Cihad; Alpaslan, Ferda Nur (2025-07-01) Efficient and effective risk management is a crucial factor for organizations as it enables in identifying and responding to potential threats that may impede the achievement of strategic organizational objectives. It help...
Damage detection in aircraft engine borescope inspection using deep learning Uzun, Ismail; Tolun, Mehmet Resit; Sari, Filiz; Alpaslan, Ferda Nur (2025-01-01) Aircraft engine inspection is a key pillar of aviation safety as it helps to maintain adequate performance standards to ensure engine airworthiness. In addition, it is also vital for asset value retention. Borescope inspec...
The reusability prior: comparing deep learning models without training Polat, Aydın Göze; Alpaslan, Ferda Nur (2023-06-01) Various choices can affect the performance of deep learning models. We conjecture that differences in the number of contexts for model components during training are critical. We generalize this notion by defining the reus...
GDPR and FAIR compliant decision support system design for triage and disease detection KARAMANLIOĞLU, ALPER; Alpaslan, Ferda Nur; Sunar, Elif Tansu; Cetin, Cihan; Akca, Gülsüm; Merdanoglu, Hakan; Dogan, Osman Tufan (2023-05-14) In this study, a novel decision support system design is proposed that addresses triage and disease detection, and automatically makes predictions on structural and semi- structural clinical data. The proposed system consi...
Learning to play an imperfect information card game using reinforcement learning Alpaslan, Ferda Nur; Baykal, Ömer; Demirdöver, Buğra Kaan (2022-08-01) Artificial intelligence and machine learning are widely popular in many areas. One of the most popular ones is gaming. Games are perfect testbeds for machine learning and artificial intelligence with various scenarios and ...
Next-Generation Payment System for Device-to-Device Content and Processing Sharing Kihtir, Fatih; Yazıcı, Mehmet Akif; Oztoprak, Kasim; Alpaslan, Ferda Nur (2022-04-01) Recent developments in telecommunication world have allowed customers to share the storage and processing capabilities of their devices by providing services through fast and reliable connections. This evolution, however, ...
Three-Dimensional Analysis of Binding Sites for Predicting Binding Affinities in Drug Design Erdas-Cicek, Ozlem; Atac, Ali Osman; Gurkan-Alp, A. Selen; Buyukbingol, Erdem; Alpaslan, Ferda Nur (American Chemical Society (ACS), 2019-11-01) Understanding the interaction between drug molecules and proteins is one of the main challenges in drug design. Several tools have been developed recently to decrease the complexity of the process. Artificial intelligence ...
Reinforcement Learning in Card Game Environments Using Monte Carlo Methods and Artificial Neural Networks Baykal, Ömer; Alpaslan, Ferda Nur (2019-09-01) Artificial intelligence has wide range of application areas and games are one of the important ones. There are many applications of artificial intelligence methods in game environments. It is very common for game environme...
Supervised Learning in Football Game Environments Using Artificial Neural Networks Baykal, Ömer; Alpaslan, Ferda Nur (2018-09-23) Game industry has become one of the sectors that commonly use artificial intelligence. Today, most of the game environments include artificial intelligence agents to offer more challenging and entertaining gameplay experie...

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