Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach

AM Gaeta, M Quijada-López, F Barbé… - Frontiers in Aging …, 2024 - frontiersin.org
Introduction Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Current
core cerebrospinal fluid (CSF) AD biomarkers, widely employed for diagnosis, require a …

Comparison of support vector regression and random forest algorithms for estimating the SOFC output voltage by considering hydrogen flow rates

FC İskenderoğlu, MK Baltacioğlu, MH Demir… - International Journal of …, 2020 - Elsevier
Abstract Solid Oxide Fuel Cell (SOFC) are complex systems in which gas-phase mass
transport, heat transfer, ionic conduction, chemical reactions and electrical conduction take …

Modular robot interface for a smart operating theater

L Prokhorenko, D Klimov, D Mishchenkov… - Journal of Robotic …, 2023 - Springer
This paper discusses the architecture and implementation of a modular component of the
smart operating theater digital twin, designed to control robotic equipment—the robot …

Detection of periodic leg movements by machine learning methods using polysomnographic parameters other than leg electromyography

I Umut, G Çentik - Computational and mathematical methods in …, 2016 - Wiley Online Library
The number of channels used for polysomnographic recording frequently causes difficulties
for patients because of the many cables connected. Also, it increases the risk of having …

Novel Wearable System to Recognize Sign Language in Real Time

İ Umut, ÜC Kumdereli - 2024 - preprints.org
The aim of this study is to develop a software solution for real-time recognition of sign
language words using two arms. This will enable communication between hearing-impaired …

EEG klavyesi tasarımı

S Büyükgöze - 2021 - dspace.trakya.edu.tr
Özet Elektroensefalografik (EEG) verilerinin, sanal klavye yazılımında nümerik karakterlerin
tahminlemesi için giriş verisi olarak kullanılıp kullanılamayacağını belirlemek üzere bu tez …