Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.
Pancreas
; 50(7): 916-922, 2021 08 01.
Article
em En
| MEDLINE
| ID: mdl-34629446
ABSTRACT
ABSTRACT The potential of artificial intelligence (AI) applied to clinical data from electronic health records (EHRs) to improve early detection for pancreatic and other cancers remains underexplored. The Kenner Family Research Fund, in collaboration with the Cancer Biomarker Research Group at the National Cancer Institute, organized the workshop entitled "Early Detection of Pancreatic Cancer Opportunities and Challenges in Utilizing Electronic Health Records (EHR)" in March 2021. The workshop included a select group of panelists with expertise in pancreatic cancer, EHR data mining, and AI-based modeling. This review article reflects the findings from the workshop and assesses the feasibility of AI-based data extraction and modeling applied to EHRs. It highlights the increasing role of data sharing networks and common data models in improving the secondary use of EHR data. Current efforts using EHR data for AI-based modeling to enhance early detection of pancreatic cancer show promise. Specific challenges (biology, limited data, standards, compatibility, legal, quality, AI chasm, incentives) are identified, with mitigation strategies summarized and next steps identified.
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
1_ASSA2030
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Pancreáticas
/
Inteligência Artificial
/
Congressos como Assunto
/
Detecção Precoce de Câncer
/
Registros Eletrônicos de Saúde
Tipo de estudo:
Diagnostic_studies
/
Guideline
/
Prognostic_studies
/
Screening_studies
Limite:
Humans
Idioma:
En
Revista:
Pancreas
Ano de publicação:
2021
Tipo de documento:
Article