crowdeeg.ca
crowdEEGcrowdEEG is a collaborative annotation tool for medical time series data. It enables groups of experts or non-expert crowds to perform feature detection or high-level classification tasks.
http://www.crowdeeg.ca/
crowdEEG is a collaborative annotation tool for medical time series data. It enables groups of experts or non-expert crowds to perform feature detection or high-level classification tasks.
http://www.crowdeeg.ca/
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crowdEEG | crowdeeg.ca Reviews
https://crowdeeg.ca
crowdEEG is a collaborative annotation tool for medical time series data. It enables groups of experts or non-expert crowds to perform feature detection or high-level classification tasks.
crowdeeg.ca
People
http://crowdeeg.ca/people
PI, University of Waterloo). PI, McGill University). PI, Sunnybrook Hospital). Pierre Thodoroff (Masters Student). Evgeny Naumov (Masters Student).
Resources
http://crowdeeg.ca/resources
Warby, S. C., Wendt, S. L., Welinder, P., Munk, E. G. S., Carrillo, O., Sorensen, H. B. D., Mignot, E. (2014). Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods. Nature Methods, 11(4), 385 392. http:/ doi.org/10.1038/nmeth.2855. Urner, R., Shai, B.-D., and Ohad, S. (2012). Learning from Weak Teachers. In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (pp. 1252 1260)&#...Bajaj, V., and Pachor...
Ongoing Studies
http://crowdeeg.ca/ongoing-studies
News
http://crowdeeg.ca/news
Apr 21, 2016. The local Toronto chapter of NeuroTechX. Arguably the largest and most vibrant global meetup community for neurotechnology, recently invited the crowdEEG team to present their work to an interested crowd of medical experts, entrepreneurs, engineers and neurotech enthusiasts.
Publications
http://crowdeeg.ca/publications
Jaini, P., Chen, Z., Carbajal, P., Law, E., Middleton, L., Regan, K., Schaekermann, M., Trimponias, G., Tung, J., and Poupart, P. (2017). Online Bayesian Transfer Learning for Sequential Data Modeling. In 5th International Conference on Learning Representations (ICLR 2017). Toulon, France. Thodoroff, P., Pineau, J., and Lim, A. (2016). Learning Robust Features using Deep Learning for Automatic Seizure Detection. In Machine Learning in Health Care. Los Angeles, CA.
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Edith Law @ U.Waterloo
http://edithlaw.ca/index.html
Assistant Professor, University of Waterloo. PhD (CMU), M.Sc. (McGill), B.Sc. (UBC). 0223 University of Toronto. Invited Talk) 05.06 CHI. 0713 MSR Faculty Summit. I am an Assistant Professor at the David R. Cheriton School of Computer Science. My work is funded by NSERC Discovery Grant as well as the NSERC-CIHR Collaborative Health Research Project (CHRP). As part of my research, we are building two platforms for scientific and medical crowdsourcing: CrowdCurio. Previously, I was a CRCS.
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Crowded World | North/South Divide
Connect with me on CouchSurfing. Read my blog at Vagabondic. Languages and Linguistics Media.
CrowdedWorlds – A dead website for disposable culture!
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crowdEEG
CrowdEEG is a collaborative annotation tool for medical time series data. It enables groups of experts or non-expert crowds to perform feature detection or high-level classification tasks.
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