Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Tetiana Biloborodova"'
Autor:
Tetiana Biloborodova, Lukasz Scislo, Inna Skarga-Bandurova, Anatoliy Sachenko, Agnieszka Molga, Oksana Povoroznyuk, Yelyzaveta Yevsieieva
Publikováno v:
Mathematical Biosciences and Engineering, Vol 18, Iss 4, Pp 4919-4942 (2021)
The fetal heart rate (fHR) variability and fetal electrocardiogram (fECG) are considered the most important sources of information about fetal wellbeing. Non-invasive fetal monitoring and analysis of fECG are paramount for clinical trials. They enabl
Externí odkaz:
https://doaj.org/article/fd1e938bcaf84c02a1f9eb155bba616d
Publikováno v:
Caring is Sharing – Exploiting the Value in Data for Health and Innovation ISBN: 9781643683881
The study proposes an integrated approach to automated cervical intraepithelial neoplasia (CIN) diagnosis in epithelial patches extracted from digital histology images. The model ensemble, combined CNN classifier, and highest-performing fusion approa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::974deb9b1fca907b38fdfc713f8f74a6
https://doi.org/10.3233/shti230220
https://doi.org/10.3233/shti230220
Autor:
Anatoliy Sachenko, Tetiana Biloborodova, Yelyzaveta Yevsieiva, Agnieszka Molgad, Inna Skarga-Bandurova, Lukasz Scislo, Oksana Povoroznjuk
Publikováno v:
Mathematical Biosciences and Engineering, Vol 18, Iss 4, Pp 4919-4942 (2021)
The fetal heart rate (fHR) variability and fetal electrocardiogram (fECG) are considered the most important sources of information about fetal wellbeing. Non-invasive fetal monitoring and analysis of fECG are paramount for clinical trials. They enabl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98c9692cd2f7ae15abfcfa7ca603544d
http://www.aimspress.com/article/doi/10.3934/mbe.2021250?viewType=HTML
http://www.aimspress.com/article/doi/10.3934/mbe.2021250?viewType=HTML
Autor:
Tetiana, Biloborodova, Inna, Skarga-Bandurova, Illia, Skarha-Bandurov, Yelyzaveta, Yevsieieva, Oleh, Biloborodov
Publikováno v:
Studies in health technology and informatics. 294
In this paper, we present an approach to improve the accuracy and reliability of ECG classification. The proposed method combines features analysis of linear and non-linear ECG dynamics. Non-linear features are represented by complexity measures of a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::ad22c637d77c775beb3a6dceb776b0b3
https://pubmed.ncbi.nlm.nih.gov/35612008
https://pubmed.ncbi.nlm.nih.gov/35612008
Autor:
Tetiana Biloborodova, Inna Skarga-Bandurova, Illia Skarha-Bandurov, Yelyzaveta Yevsieieva, Oleh Biloborodov
In this paper, we present an approach to improve the accuracy and reliability of ECG classification. The proposed method combines features analysis of linear and non-linear ECG dynamics. Non-linear features are represented by complexity measures of a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1aa63cf4af00de4f9cb1c86e4b233e20
https://doi.org/10.3233/shti220388
https://doi.org/10.3233/shti220388
Publikováno v:
Progress in Artificial Intelligence ISBN: 9783031164736
The region of interest (RoI) identification has a significant potential for yielding information about relevant histological features and is imperative to improve the effectiveness of digital pathology in clinical practice. The typical RoI is the str
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6e7b830f0ca9854dcaee773ab995aed
https://radar.brookes.ac.uk/radar/items/1e64c3d6-7324-4ccd-8dde-d3d826adc882/1/
https://radar.brookes.ac.uk/radar/items/1e64c3d6-7324-4ccd-8dde-d3d826adc882/1/
Autor:
Tetiana, Biloborodova, Inna, Skarga-Bandurova, Mark, Koverha, Illia, Skarha-Bandurov, Yelyzaveta, Yevsieieva
Publikováno v:
Studies in health technology and informatics. 287
Medical image classification and diagnosis based on machine learning has made significant achievements and gradually penetrated the healthcare industry. However, medical data characteristics such as relatively small datasets for rare diseases or imba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::6ff899076456cab631c72bf50a5962fd
https://pubmed.ncbi.nlm.nih.gov/34795070
https://pubmed.ncbi.nlm.nih.gov/34795070
Autor:
Inna, Skarga-Bandurova, Tetiana, Biloborodova, Illia, Skarha-Bandurov, Yehor, Boltov, Maryna, Derkach
Publikováno v:
Studies in health technology and informatics. 285
The paper introduces a multilayer long short-term memory (LSTM) based auto-encoder network to spot abnormalities in fetal ECG. The LSTM network was used to detect patterns in the time series, reconstruct errors and classify a given segment as an anom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::7ac40768f66319fd9f40e4b37f7051a6
https://pubmed.ncbi.nlm.nih.gov/34734866
https://pubmed.ncbi.nlm.nih.gov/34734866
Autor:
Illia Skarha-Bandurov, Inna Skarga-Bandurova, Tetiana Biloborodova, Maryna Derkach, Yehor Boltov
Publikováno v:
pHealth
The paper introduces a multilayer long short-term memory (LSTM) based auto-encoder network to spot abnormalities in fetal ECG. The LSTM network was used to detect patterns in the time series, reconstruct errors and classify a given segment as an anom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8e298addd6b5ef95b4cfac96bad6b37
https://doi.org/10.3233/shti210588
https://doi.org/10.3233/shti210588
Publikováno v:
Information and Knowledge in Internet of Things ISBN: 9783030751227
Information and Knowledge in Internet of Things
Information and Knowledge in Internet of Things
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9dc1ef0fb724f19cfc8bc197418ee8e
https://doi.org/10.1007/978-3-030-75123-4_5
https://doi.org/10.1007/978-3-030-75123-4_5