Insights, highlights and the latest news from inside Imagia
How data is collected and managed will impact future discoveries in medical artificial intelligence. This post explains the two types of data sets encountered in the clinical setting and provides the strengths and weaknesses of both, from Imagia
...Lao, Qicheng, Xiang Jiang, Mohammad Havaei, and Yoshua Bengio.IEEE Transactions on Neural Networks and Learning Systems (2021).
Imagia, a leader in artificial intelligence and personalized healthcare announced today a $7M support from Investissement Québec as part of Imagia’s last financing round. This funding supports the development of the EVIDENSTM platform a
...The process of labeling data is costly, tedious and is a very manual task tackled by humans. Current machine learning algorithms require a lot of labeled data in order to reach performance levels that are meaningful. Once, a model is trained o
...Sylvain, Tristan, Francis Dutil, Tess Berthier, Lisa Di Jorio, Margaux Luck, Devon Hjelm, and Yoshua Bengio. In 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
The application of Machine Learning (ML) in healthcare presents unique challenges. For instance, ML algorithms may require data to be migrated and shared from the same server or datacenter for developing training datasets. In a multi-center heal
...Lao, Qicheng, Xiang Jiang, and Mohammad Havaei.In Proceedings of the AAAI Conference on Artificial Intelligence (2021).
Havaei, Mohammad, Ximeng Mao, Yiping Wang, and Qicheng Lao. Submitted to medical image analysis. arXiv preprint arXiv:2012.04764 (2020).
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