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Toplam kayıt 31, listelenen: 11-20
Comparison of deep learning and conventional machine learning methods for classification of colon polyp types
(SCIENDOBOGUMILA ZUGA 32A, WARSAW, MAZOVIA, POLAND, 2021)
Determination of polyp types requires tissue biopsy during colonoscopy and then histopathological examination of the microscopic images which tremendously time-consuming and costly. The first aim of this study was to design ...
Medical infrared thermal image based fatty liver classification using machine and deep learning
(TAYLOR & FRANCIS LTD, 2023)
Non-alcoholic fatty liver disease (NAFLD) causes accumulation of excess fat in the liver affecting people who drink little to no alcohol. Non-alcoholic steatohepatitis (NASH) is an aggressive form of fatty liver disease ...
Split-attention effects in multimedia learning environments: eye-tracking and EEG analysis
(SPRINGER, 2022)
This study aimed to evaluate the split-attention effect in multimedia learning environments via objective measurements as EEG and eye-tracking. Two different multimedia
learning environments in a focused (integrated) and ...
Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization
(ELSEVIER IRELAND, 2023)
Background and Objective: Early detection of colon adenomatous polyps is critically important because correct detection of it significantly reduces the potential of developing colon cancers in the future. The key challenge ...
An FDTD-based computer simulation platform for shock wave propagation in electrohydraulic lithotripsy
(ELSEVIER, 2013)
Extracorporeal Shock Wave Lithotripsy (ESWL) is based on disintegration of the kidney stone
by delivering high-energy shock waves that are created outside the body and transmitted
through the skin and body tissues. ...
Like/dislike analysis using EEG: Determination of most discriminative channels and frequencies
(ELSEVIER IRELAND LTD, 2014)
In this study, we have analyzed electroencephalography (EEG) signals to investigate the following issues, (i) which frequencies and EEG channels could be relatively better indicators of preference (like or dislike decisions) ...
Liver fibrosis staging using CT image texture analysis and soft computing
(ELSEVIER, 2014)
Liver biopsy is considered to be the gold standard for analyzing chronic hepatitis and fibrosis; however, it is an invasive and expensive approach, which is also difficult to standardize. Medical imaging
techniques such ...
Transfer Learning for P300 Brain-Computer Interfaces by Joint Alignment of Feature Vectors
(IEEE, 2023)
This article presents a new transfer learning
method named group learning, that jointly aligns multiple domains (many-to-many) and an extension named fast
alignment that aligns any further domain to previously
aligned ...
Lung cancer subtype differentiation from positron emission tomography images
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY, 2020)
Lung cancer is one of the deadly cancer types, and almost 85% of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation ...
A new tool for QT interval analysis during sleep in healthy and obstructive sleep apnea subjects: a study on women
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY, 2013)
By monitoring the Q wave/T wave (QT) interval computed from electrocardiography (ECG) signals during sleep, it is possible to create a link between the ventricular repolarization and sleep stages. In this study, we aimed ...