Top Highlights: Latest Developments in Data News
In the ever-evolving world of technology, machine learning continues to make significant strides in various fields, with healthcare being no exception. Here are some of the latest developments that are reshaping the landscape.
Machine Learning in Healthcare
Researchers from Ariel University have developed a machine learning algorithm that identifies predictors of Opioid Use Disorder (OUD) for earlier diagnosis. The model takes into account factors such as annual opioid prescriptions, days of opioid treatment, and longer consecutive opioid prescriptions. Interestingly, it also identifies hypertension, hyperlipidemia, the number of hypertensive crisis events, and age as significant predictors for OUD.
Meanwhile, researchers from the Columbia Mailman School of Public Health have developed a model for infectious disease surveillance. This innovative model uses data streams from multiple locations and mobility data to predict the spread of diseases, even in locations that do not collect and share data.
In a groundbreaking development, researchers from the Massachusetts Institute of Technology have developed a machine learning approach for predicting the quality of biopharmaceutical products. This approach aims to decrease costs by predicting the impact processing changes will have on the product.
On a different note, a machine learning model developed by DeepHealth can detect breast cancer one year earlier than standard clinical models used by radiologists.
Alexa Custom Assistant
In the realm of consumer technology, Amazon has open-sourced its Alexa technology, allowing companies to custom-build voice assistants. The Alexa Custom Assistant is designed for responding to unique product-specific wake words and commands. It is currently offered to automobile companies in 14 countries for vehicle control software development.
The Alexa Custom Assistant is not just limited to consumer products. It can also be used for predicting what type of quality control would most accurately measure the physical, chemical, or biological quality for a specific product.
As technology continues to advance, it's clear that machine learning will play an increasingly important role in various industries, from healthcare to consumer technology. However, it's important to note that more research is needed to fully understand the implications of these advancements, especially in the field of healthcare. For instance, the search results do not provide information about which company developed the machine learning algorithm for early detection of opioid substance abuse.
These developments underscore the potential of machine learning to revolutionise our world, and it's an exciting time to be part of this technological revolution.
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