Jacek M Zurada
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Explore the profile of Jacek M Zurada including associated specialties, affiliations and a list of published articles.
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49
Citations
257
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Recent Articles
1.
Affan A, Zurada J, Inane T
Annu Int Conf IEEE Eng Med Biol Soc
. 2023 Dec;
2023:1-4.
PMID: 38083458
In the condition of anemia, kidneys produce less erythropoietin hormone to stimulate the bone marrow to make red blood cells (RBC) leading to a reduced hemoglobin (Hgb) level, also known...
2.
Fan Q, Kang Q, Zurada J, Huang T, Xu D
IEEE Trans Neural Netw Learn Syst
. 2023 Oct;
35(12):18687-18701.
PMID: 37847629
In this article, we investigate the boundedness and convergence of the online gradient method with the smoothing group regularization for the sigma-pi-sigma neural network (SPSNN). This enhances the sparseness of...
3.
Affan A, Zurada J, Inanc T
IEEE Open J Eng Med Biol
. 2023 Feb;
3:242-251.
PMID: 36846361
Warfarin is a challenging drug to administer due to the narrow therapeutic index of the International Normalized Ratio (INR), the inter- and intra-variability of patients, limited clinical data, genetics, and...
4.
Ali Meerza S, Affan A, Mirinejad H, Brier M, Zurada J, Inanc T
Annu Int Conf IEEE Eng Med Biol Soc
. 2021 Dec;
2021:5035-5038.
PMID: 34892338
Warfarin belongs to a medication class called anticoagulants or blood thinners. It is used for the treatment to prevent blood clots from forming or growing larger. Patients with venous thrombosis,...
5.
Affan A, Zurada J, Brier M, Inanc T
Annu Int Conf IEEE Eng Med Biol Soc
. 2021 Dec;
2021:4448-4451.
PMID: 34892207
Administration of drugs requires sophisticated methods to determine the drug quantity for optimal results, and it has been a challenging task for the number of diseases. To solve these challenges,...
6.
Xu F, Liu L, Zurada J, Yi Z
IEEE Trans Cybern
. 2020 Dec;
52(6):4701-4716.
PMID: 33296319
This article is concerned with the problem of the number and dynamical properties of equilibria for a class of connected recurrent networks with two switching subnetworks. In this network model,...
7.
Ayinde B, Inanc T, Zurada J
Neural Netw
. 2019 Jul;
118:148-158.
PMID: 31279285
This paper presents an efficient technique to reduce the inference cost of deep and/or wide convolutional neural network models by pruning redundant features (or filters). Previous studies have shown that...
8.
Ayinde B, Inanc T, Zurada J
IEEE Trans Neural Netw Learn Syst
. 2019 Jan;
30(9):2650-2661.
PMID: 30624232
This paper proposes a new and efficient technique to regularize the neural network in the context of deep learning using correlations among features. Previous studies have shown that oversized deep...
9.
Zhao J, Zurada J, Yang J, Wu W
Neural Netw
. 2018 Apr;
103:19-28.
PMID: 29625353
Unlike the first and the second generation artificial neural networks, spiking neural networks (SNNs) model the human brain by incorporating not only synaptic state but also a temporal component into...
10.
Wang J, Xu C, Yang X, Zurada J
IEEE Trans Neural Netw Learn Syst
. 2017 Sep;
29(5):2012-2024.
PMID: 28961129
In this paper, we propose four new variants of the backpropagation algorithm to improve the generalization ability for feedforward neural networks. The basic idea of these methods stems from the...