Decision based on big data research for non-small cell lung cancer in medical artificial system in developing country.
Comput Methods Programs Biomed
; 159: 87-101, 2018 Jun.
Article
em En
| MEDLINE
| ID: mdl-29650322
ABSTRACT
Non-small cell lung cancer (NSCLC) is a high risk cancer and is usually scanned by PET-CT for testing, predicting and then give the treatment methods. However, in the actual hospital system, at least 640 images must be generated for each patient through PET-CT scanning. Especially in developing countries, a huge number of patients in NSCLC are attended by doctors. Artificial system can predict and make decision rapidly. According to explore and research artificial medical system, the selection of artificial observations also can result in low work efficiency for doctors. In this study, data information of 2,789,675 patients in three hospitals in China are collected, compiled, and used as the research basis; these data are obtained through image acquisition and diagnostic parameter machine decision-making method on the basis of the machine diagnosis and medical system design model of adjuvant therapy. By combining image and diagnostic parameters, the machine decision diagnosis auxiliary algorithm is established. Experimental result shows that the accuracy has reached 77% in NSCLC.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Tomografia Computadorizada por Raios X
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Carcinoma Pulmonar de Células não Pequenas
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Neoplasias Pulmonares
Tipo de estudo:
Clinical_trials
/
Prognostic_studies
Limite:
Adult
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Aged
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Humans
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Middle aged
País/Região como assunto:
Asia
Idioma:
En
Revista:
Comput Methods Programs Biomed
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2018
Tipo de documento:
Article