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.
We are delighted that some of the CuraCloud team’s scientific work will be featured at the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) from September 16th to 20th 2018 in Granada, Spain.
CuraCloud is participating in the AI in Healthcare program Thursday Sept 13 at 4 pm at the Cambia Grove.
CuraCloud will be exhibiting at Society for Imaging Informatics in Medicine (SIIM) in a couple weeks.
Deep learning, data mining, machine learning and natural language processing are all trending words in artificial intelligence (AI).
CuraCloud exhibited at Radiological Society of North America (RSNA) from 11/26-30 and showcased some of their AI capabilities to enhance medical imaging workflows.
CuraCloud invites attendees of the Radiological Society of North America (RSNA) 2017 Conference to visit the CuraCloud booth to learn how to use AI to enhance medical imaging workflows.
Artificial Intelligence technologies have matured over the past few years. But are we overestimating A.I.? How exactly is it transforming the healthcare industry?
On October 5th, CuraCloud’s VP of Marketing and Corporate Development, Ed Butler, will discuss why radiology will be the first to adopt AI
The Japanese healthcare system was designed for universal access and accessibility. Japan has made significant investments in radiological imaging and has the world’s highest per capita installations of Computed Tomography (CT) imaging machines.
Xconomy’s Ben Romano reports how CuraCloud™ A.I. is being embedded in clinical workflows to expedite radiologist review of critical cases: With Triage System, Companies See Toehold for A.I. in Radiology.
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.