Visualizing X-ray Scans of COVID-19 Positive Patients

The ongoing COVID-19 public health emergency has increased the urgency of data analysis and predictive analytics in helping to effectively combat the spread of the virus, and target regions of the world that are or will be most in need. At OAITI, we like so many others have been collecting data relating to the outbreak, and trying to use this data to inform better decision-making, from individual daily actions to public policy directives.

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NLP using word2vec for Donor Matching

In our previous post, we noted how 1 and 2 grams from a query mission can be matched to donor mission statements to find an appropriate donor organization. We performed some text cleaning and used tfidf as a metric for weighting the more important words. The final results showed some issues with this method – like the word ‘heart’ in “Isreal at Heart” being matched to “heart conditions”. When we know that most words will have a context associated with their usage and the meaning of the word changes according to its context, how do we still match missions by matching words?

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Using NLP to find the perfect donor match – 1

One of the difficulties of starting a non-profit is finding donors and funding agencies. We’ve seen first hand the challenges involved! With so many different foundations with a wide variety of mission statements, how do we find one that is most closely aligned with our goals?

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