Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Focus on i2b2 Obesity NLP Challenge: Research Paper"'
Autor:
Aaron Cohen, Kyle H. Ambert
Publikováno v:
Journal of the American Medical Informatics Association. 16:590-595
Objective Free-text clinical reports serve as an important part of patient care management and clinical documentation of patient disease and treatment status. Free-text notes are commonplace in medical practice, but remain an under-used source of inf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5afb91ac24e67eb0af3c210dfbe671bc
https://doi.org/10.1197/jamia.m3095
https://doi.org/10.1197/jamia.m3095
Publikováno v:
Journal of the American Medical Informatics Association. 16:576-579
Objective Evaluate the effectiveness of a simple rule-based approach in classifying medical discharge summaries according to indicators for obesity and 15 associated co-morbidities as part of the 2008 i2b2 Obesity Challenge. Methods The authors appli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36d71743307ad64501cf716a0f867eea
https://doi.org/10.1197/jamia.m3086
https://doi.org/10.1197/jamia.m3086
Publikováno v:
Journal of the American Medical Informatics Association. 16:580-584
Objective: Automated and disease-specific classification of textual clinical discharge summaries is of great importance in human life science, as it helps physicians to make medical studies by providing statistically relevant data for analysis. This
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d58c4aa19c4a10a4cb9ee5bb1d8f6395
https://doi.org/10.1197/jamia.m3087
https://doi.org/10.1197/jamia.m3087
Autor:
Attila Almási, Veronika Vincze, Róbert Busa-Fekete, István Hegedűs, Róbert Ormándi, Richárd Farkas, György Szarvas
Publikováno v:
Journal of the American Medical Informatics Association. 16:601-605
OBJECTIVE In this study the authors describe the system submitted by the team of University of Szeged to the second i2b2 Challenge in Natural Language Processing for Clinical Data. The challenge focused on the development of automatic systems that an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::838edb02a54800e64a95dce210119f28
https://doi.org/10.1197/jamia.m3097
https://doi.org/10.1197/jamia.m3097
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA. 16(4)
OBJECTIVE The authors present a system developed for the Challenge in Natural Language Processing for Clinical Data-the i2b2 obesity challenge, whose aim was to automatically identify the status of obesity and 15 related co-morbidities in patients us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e17a458102fd2fcba269068c921cccd5
https://pubmed.ncbi.nlm.nih.gov/19390098
https://pubmed.ncbi.nlm.nih.gov/19390098
Objective: The authors developed a natural language processing (NLP) framework that could be used to extract clinical findings and diagnoses from dictated physician documentation. Design: De-identified documentation was made available by i2b2 Bio-inf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d3edee3b96d956bdf285c85bace1f2d
https://europepmc.org/articles/PMC2705264/
https://europepmc.org/articles/PMC2705264/
