Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Iuliia, Lenivtceva"'
Autor:
Aleksandr A. Khrulkov, Anastasia A. Funkner, Michil P. Egorov, Aleksandr D. Kshenin, Liubov Elkhovskaya, Iuliia Lenivtceva
Publikováno v:
Procedia Computer Science. 193:22-31
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::292451216b21765b7408ce14ec03fa20
https://doi.org/10.1016/j.procs.2021.10.003
https://doi.org/10.1016/j.procs.2021.10.003
Publikováno v:
Procedia Computer Science. 193:82-91
This article describes the results of data filtering of electronic health records for patients diagnosed with aortic aneurysm in two different medical centers to prepare data for further feature extraction. The accuracy improvement of filtered data w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::364d69a6646fe822feba0ecb6907fa8a
https://doi.org/10.1016/j.procs.2021.10.009
https://doi.org/10.1016/j.procs.2021.10.009
Publikováno v:
Journal of Personalized Medicine; Volume 12; Issue 4; Pages: 637
The complications of thoracic aortic disease include aortic dissection and aneurysm. The risks are frequently compounded by many cardiovascular comorbidities, which makes the process of clinical decision making complicated. The purpose of this study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8caaae6cb271f75d428a6991cac31a22
Preprocessing of unstructured medical data: the impact of each preprocessing stage on classification
Publikováno v:
Procedia Computer Science. 178:284-290
Nowadays, it is still important to develop methods for processing data, in particular medical texts, in Russian. In this paper, we checked how each stage of text pre-processing affects the result of the classifier. The paper analyzed 269923 records o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::567435b09fd0dba0999cf16234354dae
https://doi.org/10.1016/j.procs.2020.11.030
https://doi.org/10.1016/j.procs.2020.11.030
Publikováno v:
Studies in health technology and informatics. 285
This article describes the results of feature extraction from unstructured medical records and prediction of postoperative complications for patients with thoracic aortic aneurysm operations using machine learning algorithms. The datasets from two di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::62297411fe5044fd71f7809f5314f43b
https://pubmed.ncbi.nlm.nih.gov/34734856
https://pubmed.ncbi.nlm.nih.gov/34734856
Publikováno v:
pHealth
This article describes the results of feature extraction from unstructured medical records and prediction of postoperative complications for patients with thoracic aortic aneurysm operations using machine learning algorithms. The datasets from two di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::df6eef9430a0f5b482157c90b5d4a3f0
https://doi.org/10.3233/shti210578
https://doi.org/10.3233/shti210578
Autor:
Georgy Kopanitsa, Iuliia Lenivtceva
Publikováno v:
Methods of information in medicine. 60(3-04)
Background The larger part of essential medical knowledge is stored as free text which is complicated to process. Standardization of medical narratives is an important task for data exchange, integration, and semantic interoperability. Objectives The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df20b255be882e0ba5a5a1736363ea55
https://pubmed.ncbi.nlm.nih.gov/34425626
https://pubmed.ncbi.nlm.nih.gov/34425626
Autor:
Iuliia Lenivtceva, Georgy Kopanitsa
Publikováno v:
Methods of Information in Medicine. 58:151-159
Background Evaluating potential data losses from mapping proprietary medical data formats to standards is essential for decision making. The article implements a method to evaluate the preliminary content overlap of proprietary medical formats, inclu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93886d8366ce840e8e311def157e1f50
https://doi.org/10.1055/s-0040-1702154
https://doi.org/10.1055/s-0040-1702154
Publikováno v:
Studies in health technology and informatics. 273
The use of different data formats complicates the standardization and exchange of valuable medical data. Moreover, a big part of medical data is stored as unstructured medical records that are complicated to process. In this work we solve the task of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::33a1571f5c5746674e8d87649a9d1beb
https://pubmed.ncbi.nlm.nih.gov/33087608
https://pubmed.ncbi.nlm.nih.gov/33087608
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030504229
ICCS (4)
ICCS (4)
Structuring medical text using international standards allows to improve interoperability and quality of predictive modelling. Medical text classification task facilitates information extraction. In this work we investigate the applicability of sever
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b691d9b650552e4f96328744308f000
https://doi.org/10.1007/978-3-030-50423-6_38
https://doi.org/10.1007/978-3-030-50423-6_38