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machine learning

The algorithm uses age, sex, and information about troponin concentrations in patients to determine the likelihood of a heart attack.  

A JAMA study found that low-value diagnostic tests are common in inpatient settings, and machine learning systems can be used to identify those tests and reduce their overutilization.

The San Francisco-based microbial genomics firm will sell off its product lines, testing labs, IP, and data within the next three months.

The firm said it will use the funding to invest in research and development that will improve upon its deep shotgun metagenomic sequencing technology.

Beyond its HostDx Sepsis test, the firm is working on a test to detect and differentiate bacterial from viral infections in patients presenting with fever.

The financing, led by Accelerated Digital Ventures, will go toward the development of 20 tests targeted at cancers and dementias.

Rutgers researchers have developed a point-of-care tool that can rapidly assess the sensitivity of tumor cells to cancer drugs without staining or labeling.

Israel-based software company Medial EarlySign will work with Geisinger's innovation center to develop technologies to predict lower GI and other "high-burden" diseases.

The company's new KidneyCare test will include AlloSure for rejection, AlloMap for quiescence, and Cibiltech's AI algorithm for graft health information.

The company plans to present early data this year from its collaboration with Johnson & Johnson to develop a nasal swab-based lung cancer genomic classifier.

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