Automated Identification and Measurement Extraction of Pancreatic Cystic Lesions from Free-Text Radiology Reports Using Natural Language Processing-Reference-Cited by-同舟云学术

Automated Identification and Measurement Extraction of Pancreatic Cystic Lesions from Free-Text Radiology Reports Using Natural Language Processing

Published:2022-03-01 Issue:2 Volume:4 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Yamashita Rikiya¹^ORCID,Bird Kristen¹,Cheung Philip Yue-Cheng¹,Decker Johannes Hugo¹^ORCID,Flory Marta Nicole¹^ORCID,Goff Daniel¹^ORCID,Morimoto Linda Nayeli¹,Shon Andy¹,Wentland Andrew Louis¹^ORCID,Rubin Daniel L.¹^ORCID,Desser Terry S.¹^ORCID

Affiliation:

1. From the Departments of Biomedical Data Science (R.Y., D.L.R.) and Radiology (K.B., P.Y.C.C., J.H.D., M.N.F., D.G., L.N.M., A.S., A.L.W., D.L.R., T.S.D.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305.

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.210092

Reference18 articles.

1. Pancreatic Cyst Prevalence and the Risk of Mucin-Producing Adenocarcinoma in US Adults

2. Management of Incidental Pancreatic Cysts: A White Paper of the ACR Incidental Findings Committee

3. Management of Pancreatic Cysts in an Evidence-Based World

4. Automated pancreatic cyst screening using natural language processing: a new tool in the early detection of pancreatic cancer

5. Characterization of patients with advanced chronic pancreatitis using natural language processing of radiology reports

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