CuraCloud’s mission is to collaboratively develop medical AI solutions with healthcare delivery organizations, medical technology leaders, and pharmaceutical companies to improve diagnostics, care processes, and clinical outcomes.
CuraCloud is an international medical AI R&D company developing software medical devices and providing professional services to medical technology vendors, healthcare organizations, and pharmaceutical companies. Our machine learning scientists, software engineers, and designers collaborate with leading medical centers around the world to apply the latest advances in machine learning, medical informatics, and regulatory science to improve human health.
Since 2016, we have been applying our AI expertise to some of the most challenging problems in healthcare. Many of our team members worked together for over ten years before starting CuraCloud, developing advanced technologies for leading companies around the world.
Today, we work closely with our clinical collaboration partners to create scalable and compliant medical solutions. We also work with in-house clinicians and external radiology advisers to help us navigate the clinical workflow and define clinical use cases.
VP Corporate Development
Xiaoxiao Liu, PhD
Director of Products & Services
Youbing Yin, PhD
VP of R&D
Simultaneous Classification and Segmentation of Intracranial Hemorrhage Using a Fully Convolutional Neural Network
Guo, D., Wei, H., Zhao, P., Pan, Y, et al.
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.
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.
DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction
Guo Z, Bai J, Lu Y, Wang X, Cao K, et al.,
International Conference on Information Processing in Medical Imaging (IPMI), 2019.
Residual Attention Based Network for Hand Bone Age Assessment
Wu E, Kong B, Wang X, Bai J, Lu Y, et al.,
IEEE International Symposium on Biomedical Imaging (ISBI), 2019.
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