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Using Machine Learning Models in Diagnostic Testing

March 7, 2022 / Melody Smith / Comments Off on Using Machine Learning Models in Diagnostic Testing

Researchers have developed an automated method using machine learning to predict the effectiveness of viral diagnostic tests and designs optimized ones. This interesting news came to us from Phys.org in their article, “Machine learning could help scientists design better viral diagnostics.”

ADAPT uses trained algorithms to predict the best sequences for a diagnostic, promises to help scientists rapidly design tests that are more effective for a large number of different viruses and can be quickly modified and scaled as viruses evolve.

Machine learning is becoming a commodity. Numerous machine learning frameworks and services are available to data holders who are not experts but want to train predictive models on their data.

Interestingly, most organizations have little knowledge on how artificial intelligence (AI) systems make the decisions they do, and as a result, how the results are being applied in the various fields that AI and machine learning are being applied. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.

Melody K. Smith

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Melody Smith

Melody K. Smith has provided organizational, social media and digital communication services to a large non-profit for the past twenty years. Prior to that she championed employee engagement and communications in the healthcare field. She holds a Bachelors degree in Marketing. When not wrangling and writing TaxoDiary content for your reading pleasure, Melody writes fiction, rescues dogs and throws legendary dinner parties.