STM Publishing
Parity Computing employs artificial intelligence to transform raw STM content into high-accuracy disambiguation, profiling, and recommendation applications for publishers and researchers.
Healthcare
Parity develops novel machine learning algorithms for multivariate predictors on genomic and clinical data. Parity’s methods avoid overfitting problems that prevent conventional approaches from generalizing to new data.
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Publisher: "From my vast corpus of content, how can I use emerging AI techniques to derive new high-value insights for my users?"
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Researcher: "Which grant-awarding bodies are most likely to fund my project, and which journals are best suited to publish my results?"
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Geneticist: "Which gene variants are most likely associated with the symptoms displayed by my undiagnosed patient?"
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Pharma Company: "Based on their genome, which patients are most likely to experience good results from our cancer therapies?"
