Artificial Intelligence in Lung Cancer: Bridging the Gap Between Computational Power and Clinical Decision-Making.
Can Assoc Radiol J
; 72(1): 86-97, 2021 Feb.
Article
em En
| MEDLINE
| ID: mdl-32735493
ABSTRACT
Lung cancer remains the most common cause of cancer death worldwide. Recent advances in lung cancer screening, radiotherapy, surgical techniques, and systemic therapy have led to increasing complexity in diagnosis, treatment decision-making, and assessment of recurrence. Artificial intelligence (AI)-based prediction models are being developed to address these issues and may have a future role in screening, diagnosis, treatment selection, and decision-making around salvage therapy. Imaging plays an essential role in all components of lung cancer management and has the potential to play a key role in AI applications. Artificial intelligence has demonstrated value in prognostic biomarker discovery in lung cancer diagnosis, treatment, and response assessment, putting it at the forefront of the next phase of personalized medicine. However, although exploratory studies demonstrate potential utility, there is a need for rigorous validation and standardization before AI can be utilized in clinical decision-making. In this review, we will provide a summary of the current literature implementing AI for outcome prediction in lung cancer. We will describe the anticipated impact of AI on the management of patients with lung cancer and discuss the challenges of clinical implementation of these techniques.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
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Diagnóstico por Imagem
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Interpretação de Imagem Assistida por Computador
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Tomada de Decisão Clínica
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Neoplasias Pulmonares
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Can Assoc Radiol J
Assunto da revista:
RADIOLOGIA
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Canadá