Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Rosa L. Figueroa"'
Publikováno v:
IEEE Access, Vol 9, Pp 38767-38777 (2021)
Biomedical text classification algorithms, which currently support clinical decision-making processes, call for expensive training texts due to the low availability of labeled corpus and the cost of manual annotation by specialized professionals. The
Externí odkaz:
https://doaj.org/article/4360ab3ce6894d639c0ccf0c326fe88f
Publikováno v:
IEEE Access, Vol 8, Pp 29270-29280 (2020)
High accuracy text classifiers are used nowadays in organizing large amounts of biomedical information and supporting clinical decision-making processes. In medical informatics, regular expression-based classifiers have emerged as an alternative to t
Externí odkaz:
https://doaj.org/article/ec7b9e1fca964e9eba4b39c1c3781981
Autor:
Andres Alejandro Ramos Magna, Hector Allende-Cid, Carla Taramasco, Carlos Becerra, Rosa L. Figueroa
Publikováno v:
IEEE Access, Vol 8, Pp 106198-106213 (2020)
Currently, one of the main challenges for information systems in healthcare is focused on support for health professionals regarding disease classifications. This work presents an innovative method for a recommendation system for the diagnosis of bre
Externí odkaz:
https://doaj.org/article/58bb1c42e9e24228953a2127e3837ed2
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0301523 (2024)
IntroductionThe rise of new technologies in the field of health is yielding promising results. In certain chronic conditions such as type 2 diabetes mellitus, which ranks among the top five causes of global mortality, it could be useful in supporting
Externí odkaz:
https://doaj.org/article/549792f5db01408ca43f679ec0796e9c
Autor:
Carlos Becerra, Héctor Allende-Cid, Andres Alejandro Ramos Magna, Carla Taramasco, Rosa L. Figueroa
Publikováno v:
IEEE Access, Vol 8, Pp 106198-106213 (2020)
Currently, one of the main challenges for information systems in healthcare is focused on support for health professionals regarding disease classifications. This work presents an innovative method for a recommendation system for the diagnosis of bre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15c94add652e313ffe48681e8506d606
https://ieeexplore.ieee.org/document/9108225/
https://ieeexplore.ieee.org/document/9108225/
Publikováno v:
IEEE Access, Vol 8, Pp 29270-29280 (2020)
High accuracy text classifiers are used nowadays in organizing large amounts of biomedical information and supporting clinical decision-making processes. In medical informatics, regular expression-based classifiers have emerged as an alternative to t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06897e70b2f1d4c70eea107a85ebfa2d
https://ieeexplore.ieee.org/document/8985344/
https://ieeexplore.ieee.org/document/8985344/
Publikováno v:
EMBC
In this work, we present FREGEX a method for automatically extracting features from biomedical texts based on regular expressions. Using Smith-Waterman and Needleman-Wunsch sequence alignment algorithms, tokens were extracted from biomedical texts an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e6eb89514f822cf4c01d4b6ac7bf732
https://pubmed.ncbi.nlm.nih.gov/31947233
https://pubmed.ncbi.nlm.nih.gov/31947233
Publikováno v:
Computers in Biology and Medicine. 43:1628-1636
In this paper we apply independent component analysis (ICA) followed by second order blind identification (SOBI) to an atrial fibrillation (AF) 12-lead electrocardiogram (ECG) recording in order to extract the source that represents atrial activity (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0662856c26b1d8e31a3dffb8fecaf8d
https://doi.org/10.1016/j.compbiomed.2013.08.002
https://doi.org/10.1016/j.compbiomed.2013.08.002
Publikováno v:
Journal of medical systems. 40(8)
Obesity is a chronic disease with an increasing impact on the world's population. In this work, we present a method of identifying obesity automatically using text mining techniques and information related to body weight measures and obesity comorbid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53f403820c29305c980576ec8db9033d
https://pubmed.ncbi.nlm.nih.gov/27402260
https://pubmed.ncbi.nlm.nih.gov/27402260
Publikováno v:
Journal of the American Medical Informatics Association. 19:809-816
Objective This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks. Design Three existing active learning algorithms (distance-based (DIST), diversity-based (DIV),
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdd7942d2a410e47192faa37b959cff1
https://doi.org/10.1136/amiajnl-2011-000648
https://doi.org/10.1136/amiajnl-2011-000648