Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation.
Journal:
The Lancet. Digital health
PMID:
33328124
Abstract
BACKGROUND: The diagnostic performance of CT for pancreatic cancer is interpreter-dependent, and approximately 40% of tumours smaller than 2 cm evade detection. Convolutional neural networks (CNNs) have shown promise in image analysis, but the networks' potential for pancreatic cancer detection and diagnosis is unclear. We aimed to investigate whether CNN could distinguish individuals with and without pancreatic cancer on CT, compared with radiologist interpretation.
Authors
Keywords
Aged
Contrast Media
Deep Learning
Diagnosis, Differential
Female
Humans
Male
Middle Aged
Pancreas
Pancreatic Neoplasms
Racial Groups
Radiographic Image Enhancement
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Retrospective Studies
Sensitivity and Specificity
Taiwan
Tomography, X-Ray Computed