Become a sponsor to Joseph Paul Cohen
My goal is to democratize access to healthcare to provide the highest quality healthcare to everyone (specifically those not served by the current system; 8% in the US and 25% globally). Automation and AI can increase the supply of providers to fill this need. I am working to identify and overcome issues limiting the deployment of AI tools in healthcare. My core research directions are representation learning, generalization, and model interpretability.
1 sponsor has funded ieee8023’s work.
Featured work
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mlmed/torchxrayvision
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
Jupyter Notebook 944 -
ieee8023/blindtool
BlindTool – A mobile app that gives a "sense of vision" to the blind with deep learning
Java 12 -
ieee8023/covid-chestxray-dataset
We are building an open database of COVID-19 cases with chest X-ray or CT images.
Jupyter Notebook 3,005 -
ieee8023/NeuralNetwork-Examples
The same small networks implemented in different frameworks
Jupyter Notebook 70 -
mlmed/chester-xray
Chester the AI Radiology Assistant
JavaScript 160 -
ieee8023/countception
Count-Ception: Counting by Fully Convolutional Redundant Counting
Jupyter Notebook 52