Zegami highlights new insights in crowdsourced COVID-19 dataset. Cutting edge AI and visualisation technology can speed up efforts by researchers to develop new tools for diagnosis
The collection explores image similarity comparison of oesophageal cancer video frames to find cancer lesions to train the ML model
This collection shows an example of using unsupervised machine learning to predict heart disease using images derived from echocardiogram data
Our new Colour by Column feature is a powerful new dimension to visual data exploration in Zegami, enabling richer views, which reveal more of the underlying patterns in your data.
Expenditure on big data analytics generally in healthcare is estimated to see a compound annual growth rate of over 19%
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