RSNA-MICCAI Panel Discussion: 2. Leveraging the Full Potential of AI-Radiologists and Data Scientists Working Together.

Marius George LinguraruLena Maier-HeinRonald M Summers Charles E Kahn

Published in: Radiology. Artificial intelligence (2021)

In March 2021, the Radiological Society of North America hosted a virtual panel discussion with members of the Medical Image Computing and Computer Assisted Intervention Society. Both organizations share a vision to develop radiologic and medical imaging techniques through advanced quantitative imaging biomarkers and artificial intelligence. The panel addressed how radiologists and data scientists can collaborate to advance the science of AI in radiology. Keywords: Adults and Pediatrics, Segmentation, Feature Detection, Quantification, Diagnosis/Classification, Prognosis/Classification © RSNA, 2021.

Keyphrases

artificial intelligence
deep learning
big data
machine learning
high resolution
convolutional neural network
healthcare
randomized controlled trial
electronic health record
fluorescence imaging
risk assessment
human health
sensitive detection