Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 4 de 4
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
Stud Health Technol Inform ; 264: 1439-1440, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438170

RESUMO

Clinical terms are noisy descriptions typed by healthcare professionals in Spanish language in the electronic health record system (EHR). Thus, an evaluation of terminology search engine that extends SNOMED CT and an approach that uses historical data of clinical terms is described. We show how to measure precision and recall using historical search data, and we show how the performance of the search engine can be improved significantly using the technology available in the search engine.


Assuntos
Registros Eletrônicos de Saúde , Ferramenta de Busca , Idioma , Systematized Nomenclature of Medicine
2.
Stud Health Technol Inform ; 264: 1564-1565, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438233

RESUMO

ICD-10 (International Classification of Diseases 10th revision) is a classification code for diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases. This paper describes an automatic information retrieval approach to map free-text disease descriptions to ICD-10 codes. We use the Hospital Italiano de Buenos Aires (HIBA) terminology data mapped to ICD-10 codes as indexed data to find an appropriate ICD-10 code using search engine similarity metrics.


Assuntos
Armazenamento e Recuperação da Informação , Classificação Internacional de Doenças , Processamento Eletrônico de Dados , Ferramenta de Busca
3.
Stud Health Technol Inform ; 264: 1761-1762, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438331

RESUMO

Clinical documentation in healthcare institutions is one of the daily tasks that consumes most of the time for those involved. The adoption of mobile devices in medical practice increases efficiency among healthcare professionals. We describe the design and evaluation of an automatic speech recognition system that enables the transcription of audio to text of clinical notes in a mobile environment. Our system achieved 94.1% word accuracy when evaluated on pediatrics, internal medicine and surgery services.


Assuntos
Percepção da Fala , Documentação , Eficiência , Pessoal de Saúde , Humanos
4.
Stud Health Technol Inform ; 247: 915-919, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29678094

RESUMO

We describe an approach to select semantically coherent specialty subsets based on the historical use of terminology by different service areas. Our approach uses rule-based and machine learning techniques to obtain a reduced set of 29 specialties.


Assuntos
Aprendizado de Máquina , Semântica , Terminologia como Assunto , Sistemas Computacionais , Humanos
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...