Last month, I attended the 2019 Canopy Partners Imaging Summit in Raleigh, NC. The theme of this year’s event was Tipping Point: How to Maintain Your Competitive Edge in Radiology.
This summer is an exciting time to be working in medical imaging AI. I have been thinking about three new developments that may have profound implications for patients, care delivery organizations, and medical AI developers in the months ahead.
CuraCloud will be exhibiting at Society for Imaging Informatics in Medicine (SIIM) Annual Meeting from June 26 to June 28 at Gaylord Rockies Resort and Convention Center in Aurora, CO.
CuraCloud’s most recent research paper entitled “Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network” has been accepted for publication in European Radiology.
CuraCloud’s most recent research paper entitled “DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction” has been accepted for presentation at Information Processing in Medical Imaging (IPMI) 2019 in Hong Kong.
The problem addressed in this white paper is the challenge of applying formal systems development processes to collaborative development of Artificial Intelligence (AI) in healthcare.
NEW Learn to be Uncertain: Leveraging Uncertain Labels in Chest X-rays with Bayesian Neural Networks
Yang HY, Yang J, Pan Y, Cao K, Song Q, et al.,
Uncertainty and Robustness in Deep Visual Learning Workshop, IEEE Conference on Computer Vision and Pattern Recognition, June, 2019.
NEW Precise Diagnosis of Intracranial Hemorrhage and Subtypes Using a Three-dimensional Joint Convolutional and Recurrent Neural Network
Ye H*, Gao F* (*Equal contribution), Yin Y, Guo D, Zhao P, et al.,
European Radiology, March, 2019.
Guo Z, Bai J, Lu Y, Wang X, Cao K, et al.,
International conference on Information Processing in Medical Imaging (IPMI), 2019.