Artificial intelligence and radiomics enhance the positive predictive value of digital chest tomosynthesis for lung cancer detection within SOS clinical trial.

Journal: European radiology

Published Date: Mar 12, 2020

Abstract

OBJECTIVE: To enhance the positive predictive value (PPV) of chest digital tomosynthesis (DTS) in the lung cancer detection with the analysis of radiomics features.

Authors

Stephane Chauvie

Medical Physics Division, Santa Croce e Carle Hospital, Cuneo, Italy.
Adriano De Maggi

Medical Physics Division, Santa Croce e Carle Hospital, via Coppino 26, 12100, Cuneo, Italy.
Ilaria Baralis

Radiology Division, Santa Croce e Carle Hospital, Cuneo, Italy.
Federico Dalmasso

Medical Physics Division, Santa Croce e Carle Hospital, via Coppino 26, 12100, Cuneo, Italy.
Paola Berchialla

Medical Statistics Unit, Department of Clinical and Biological Sciences, University of Torino, Italy.
Roberto Priotto

Radiology Division, Santa Croce e Carle Hospital, Cuneo, Italy.
Paolo Violino

Radiology Division, Santa Croce e Carle Hospital, Cuneo, Italy.
Federico Mazza

Thoracic Surgery Division, Santa Croce e Carle Hospital, Cuneo, Italy.
Giulio Melloni

Thoracic Surgery Division, Santa Croce e Carle Hospital, Cuneo, Italy.
Maurizio Grosso

Radiology Division, Santa Croce e Carle Hospital, Cuneo, Italy.

Keywords

Aged Algorithms Artificial Intelligence Early Detection of Cancer Humans Image Processing, Computer-Assisted Logistic Models Lung Neoplasms Machine Learning Middle Aged Neural Networks, Computer Radiology Reproducibility of Results Semantics Tomography, X-Ray Computed

External Resources

View on PubMed Access via DOI PubMed (32166491)

Artificial intelligence and radiomics enhance the positive predictive value of digital chest tomosynthesis for lung cancer detection within SOS clinical trial.

Abstract

Authors

Keywords

External Resources

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