Blog Archives

Why We Invest in healthcare.ai

April 22, 2018
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­­­­We started healthcare.ai in late 2016 to bring machine learning (ML) to the healthcare masses. As we release version 2.0 of the software (on April 20th), it’s worth stepping back to fully understand why we invest in this open-source project, which is freely available to all. Why would a for-profit firm spend time investing in The post Why We...

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The Dangers of Commoditized Machine Learning in Healthcare: 5 Key Differentiators that Lead to Success

March 28, 2018
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The Dangers of Commoditized Machine Learning in Healthcare: 5 Key Differentiators that Lead to Success

Machine learning’s popularity in healthcare is growing thanks to its expanding capabilities in medical image analysis, predictive analytics, and prescriptive analytics for clinical decision support. The machine-learning-as-a-service market is expected to grow to almost $5.4 billion by 2022, with healthcare certainly being one of the industries driving that trend. Even today, many technology companies already The post The Dangers...

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Google’s Latest Efforts to Help Healthcare

March 14, 2018
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tl;dr: Healthcare needs practical machine learning tools; the focus on deep learning and GPUs doesn’t help the average health system. Background Google just released a paper called “Scalable and accurate deep learning for electronic health records” that has received deserved acclaim in both the machine learning (ML) and healthcare communities. This research comes from the The post Google’s Latest...

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Patient impact predictor–the new suggestive guidance in healthcare.ai

January 25, 2018
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Last summer we discussed the simplified interface of the 1.0 CRAN release of healthcare.ai-R, and we’re now thrilled to demo new features related to clinician guidance in the 1.2 version. We’re calling this Patient Impact Predictor (PIP). Understanding an ML model This week we’d like to highlight new functionality that allows one to go a The post Patient impact...

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