Zobrazeno 1 - 8
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pro vyhledávání: '"Karol Antczak"'
Autor:
Karol Antczak
Publikováno v:
Computer Science and Mathematical Modelling. :13-18
The paper discusses regularization properties of artificial data for deep learning. Artificial datasets allow to train neural networks in the case of a real data shortage. It is demonstrated that the artificial data generation process, described as i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f6617eeee6c6e08d30f975bff78ded7
https://doi.org/10.5604/01.3001.0013.6599
https://doi.org/10.5604/01.3001.0013.6599
Autor:
Karol Antczak
Publikováno v:
National Information Processing Institute
Generative Adversarial Networks (GAN) are known to produce synthetic data that are difficult to discern from real ones by humans. In this paper we present an approach to use GAN to produce realistically looking ECG signals. We utilize them to train a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17c33a80b0eacbdf63d241d8bf5c5bf7
http://arxiv.org/abs/2009.02700
http://arxiv.org/abs/2009.02700
Autor:
Karol Antczak
Publikováno v:
Computer Information Systems and Industrial Management ISBN: 9783030476786
CISIM
CISIM
Representation learning algorithms have recently led to a significant progress in knowledge extraction from network structures. In this paper, a representation learning framework for the medical diagnosis domain is proposed. It is based on a heteroge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffa6d6aae42e9ca70c79bffa07494ee9
https://doi.org/10.1007/978-3-030-47679-3_17
https://doi.org/10.1007/978-3-030-47679-3_17
Autor:
Karol Antczak
Publikováno v:
Computer Science and Mathematical Modelling. :5-12
Classification methods have multiple applications, with medical diagnosis being one of the most common. A powerful way to improve classification quality is to combine single classifiers into an ensemble. One of the approaches for creating such ensemb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96d39ee54855ddcdaa52ad3552bc459e
https://doi.org/10.5604/01.3001.0009.4412
https://doi.org/10.5604/01.3001.0009.4412
Autor:
Łukasz Liberadzki, Karol Antczak
Publikováno v:
MATEC Web of Conferences, Vol 210, p 04001 (2018)
Recent popularity of deep learning methods inspires to find new applications for them. One of promising areas is medical diagnosis support, especially analysis of medical images. In this paper we explore the possibility of using Deep Convolutional Ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::252836ea12d1916051b7fe2e81ea94e3
https://doaj.org/article/344577af2eb84bbf8f533518a9285277
https://doaj.org/article/344577af2eb84bbf8f533518a9285277
Autor:
Elizabeth Cummings, Karol Antczak
Publikováno v:
BJPsych bulletin. 41(6)
Thank you for this excellent and concise article outlining the complexities involved in neuroleptic malignant syndrome (NMS) in association with atypical antipsychotics.[1][1] It serves as a reminder of how guidelines and diagnostic criteria can, for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6499d4c84d9cd81460d555358d3477bc
https://pubmed.ncbi.nlm.nih.gov/29234520
https://pubmed.ncbi.nlm.nih.gov/29234520
Publikováno v:
MATEC Web of Conferences, Vol 125, p 04003 (2017)
Evaluation of classifiers in diagnosis support systems is a non-trivial task. It can be done in a form of controlled and blinded clinical trial, which is often difficult and costly. We propose a new method for generating artificial medical cases from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::352956a3a485761047b91756414dbe23
https://doi.org/10.1051/matecconf/201712504003
https://doi.org/10.1051/matecconf/201712504003
Autor:
Karol Antczak, Andrzej Walczak
Publikováno v:
MATEC Web of Conferences, Vol 76, p 04006 (2016)
The development of the Internet technology has caused telemedicine diagnosis systems to be commonly available. The most crucial aspect of the patient’s safety in such systems is a problem of safe diagnosis. There are two factors at the stake here.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b60ada2298813e47406ce9fcbda67eb3
https://doi.org/10.1051/matecconf/20167604006
https://doi.org/10.1051/matecconf/20167604006