machine learning software

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Affordable COVID-19 Diagnoses for Hospitals: How Open Source Software Helps

The most common COVID-19 symptoms—such as coughing, fever, and shortness of breath—are shared with many other diseases. Diagnosing a patient accurately is therefore a challenge. Although a diagnosis of COVID-19 might not affect treatment, it would help a hospital predict a patient's trajectory and anticipate the need for urgent intervention. But current tests, relying on blood or mucus samples, are not particularly accurate. In this article, we'll see how open source software can help hospitals make better diagnoses. I'll concentrate on one specific role, and on the ways open source facilitates finding a solution and keeping it affordable. Many aspects of the problem feed into the solution discussed here. The article is based on work by researcher Trevor Grant.

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Machine Learning in Healthcare: Part 3 - Time for a Hands-On Test

Every inpatient and outpatient EHR could theoretically be integrated with a machine learning platform to generate predictions, in order to alert clinicians about important events such as sepsis, pulmonary emboli, etc. This approach may become essential when genetic information is also included in the EHR which would mandate more advanced computation. However, using machine learning and artificial intelligence (AI) in every EHR will be a significant undertaking because not only do subject matter experts and data scientists need to create and validate the models, they must be re-tested over time and tested in a variety of patient populations. Models could change over time and might not work well in every healthcare system. Moreover, the predictive performance must be clinically, and not just statistically significant, otherwise, they will be another source of “alert fatigue.”

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