Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Barua, PD"'
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental condition worldwide. In this research, we used an ADHD electroencephalography (EEG) dataset containing more than 4000 EEG signals. Moreover, these EEGs are noisy signals.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::9dc9dceca2517a810ddc95324e3c41d5
https://hdl.handle.net/10453/164241
https://hdl.handle.net/10453/164241
Autor:
Kaplan, E, Chan, WY, Dogan, S, Barua, PD, Bulut, HT, Tuncer, T, Cizik, M, Tan, R-S, Acharya, UR
Ultrasound (US) is an important imaging modality used to assess breast lesions for malignant features. In the past decade, many machine learning models have been developed for automated discrimination of breast cancer versus normal on US images, but
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::ac0992af15d6a2a012de1ddad32eaaa4
https://hdl.handle.net/10453/170961
https://hdl.handle.net/10453/170961
PROBLEM: Cough-based disease detection is a hot research topic for machine learning, and much research has been published on the automatic detection of Covid-19. However, these studies are useful for the diagnosis of different diseases. AIM: In this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::c66579bf56bdb2e43f6063176ca31384
https://hdl.handle.net/10453/171045
https://hdl.handle.net/10453/171045
Autor:
Dogan, S, Barua, PD, Baygin, M, Chakraborty, S, Ciaccio, EJ, Tuncer, T, Abd Kadir, KA, Md Shah, MN, Azman, RR, Lee, CC, Ng, KH, Acharya, UR
This study aims to introduce a hand-crafted machine learning method to classify ischemic and hemorrhagic strokes with satisfactory performance. In the first step of this work, a new CT brain for images dataset was collected for stroke patients. A hig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::a7dc25e5e923fecc03f85d291466fe49
https://hdl.handle.net/10453/168572
https://hdl.handle.net/10453/168572
Autor:
Gudigar, A, Raghavendra, U, Samanth, J, Vasudeva, A, Ashwal, AJ, Nayak, K, Tan, RS, Ciaccio, EJ, Ooi, CP, Barua, PD, Molinari, F, Acharya, UR
The fetal echocardiogram is useful for monitoring and diagnosing cardiovascular diseases in the fetus in utero. Importantly, it can be used for assessing prenatal congenital heart disease, for which timely intervention can improve the unborn child’
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::ba1c3483559b81cf4344cdb0369750ed
https://hdl.handle.net/10453/168575
https://hdl.handle.net/10453/168575
BACKGROUND AND PURPOSE: Machine learning models have been used to diagnose schizophrenia. The main purpose of this research is to introduce an effective schizophrenia hand-modeled classification method. METHOD: A public electroencephalogram (EEG) sig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::71a75a9d17a0adeaed0cc47656c900c5
https://hdl.handle.net/10453/167830
https://hdl.handle.net/10453/167830
Recently, deep models have been very popular because they achieve excellent performance with many classification problems. Deep networks have high computational complexities and require specific hardware. To overcome this problem (without decreasing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::88c23a1b2b947170b88d04bb70c42040
https://hdl.handle.net/10453/167394
https://hdl.handle.net/10453/167394
Autor:
Barua, PD, Chan, WY, Dogan, S, Baygin, M, Tuncer, T, Ciaccio, EJ, Islam, N, Cheong, KH, Shahid, ZS, Acharya, UR
Optical coherence tomography (OCT) images coupled with many learning techniques have been developed to diagnose retinal disorders. This work aims to develop a novel framework for extracting deep features from 18 pre-trained convolutional neural netwo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::0cd410c2dd72c091e70a58fdd1f8f899
https://hdl.handle.net/10453/157291
https://hdl.handle.net/10453/157291