Advances in single-cell omics allow for unprecedented insights into the transcription profiles of individual cells.
1 code implementation • 7 Feb 2022 • Paul Bertin, Jarrid Rector-Brooks, Deepak Sharma, Thomas Gaudelet, Andrew Anighoro, Torsten Gross, Francisco Martinez-Pena, Eileen L. Tang, Suraj M S, Cristian Regep, Jeremy Hayter, Maksym Korablyov, Nicholas Valiante, Almer van der Sloot, Mike Tyers, Charles Roberts, Michael M. Bronstein, Luke L. Lairson, Jake P. Taylor-King, Yoshua Bengio
For large libraries of small molecules, exhaustive combinatorial chemical screens become infeasible to perform when considering a range of disease models, assay conditions, and dose ranges.
1 code implementation • 31 Oct 2021 • Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin, Paul Morrison, Parsa Torabian, Matteo Guarrera, Matthew P Lungren, Akshay Chaudhari, Rupert Brooks, Mohammad Hashir, Hadrien Bertrand
TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models.
Epistemic Uncertainty is a measure of the lack of knowledge of a learner which diminishes with more evidence.
Gene interaction graphs aim to capture various relationships between genes and represent decades of biology research.
Gene interaction graphs aim to capture various relationships between genes and can represent decades of biology research.
In order to bridge the gap between Deep Learning researchers and medical professionals we develop a very accessible free prototype system which can be used by medical professionals to understand the reality of Deep Learning tools for chest X-ray diagnostics.