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This post introduces Computational Hypergraph Discovery (CHD), a novel method for uncovering unknown functional relationships between variables within datasets. We’ll demonstrate the CHD approach with a practical application, the Sachs Gene DataSet. To bridge the gap between the theory from our paper and practice, we provide code snippets that help translate the underlying mathematical principles into actionable steps for data analysis. Read more
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Published in Digital Biomarkers, 2023
My first paper ! This paper describes the work we did at Doc.ai for ShareCare on Myasthenia gravis (MG) with UCB. We devellopped a Deep Learning model based on ResNet50 to predict a key symptom of MG via selfie. This would allow clinical trials to accept more patients as part of a study in order to scale it, as well as follow almost in real time the evolution of a patients symptoms using an app on their phone. Read more
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Published in Arxiv, 2023
This post introduces Computational Hypergraph Discovery (CHD), a novel method for uncovering unknown functional relationships between variables within datasets, And represent them using a hypergraph. Read more
Download here
Published:
My talk on Computational Hypergraph discovery! I have given versions of this talk at:
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.