Top Headlines: Data Digest - This Week's Compelling Info Insights

In the realm of healthcare and technology, researchers are making significant strides in the application of machine learning to improve diagnosis, prediction, and surveillance.

Researchers from Columbia Mailman School of Public Health have developed a model for infectious disease surveillance. This model, which uses data streams from multiple locations and mobility data, aims to forecast the spread of infectious respiratory diseases more accurately.

Meanwhile, Israeli researchers from Ariel University have developed a machine learning algorithm to identify predictors of opioid use disorder for earlier diagnosis. The algorithm identifies factors such as annual opioid prescriptions, days of opioid treatment, and longer consecutive opioid prescriptions as significant predictors for OUD. However, as of now, there is no specific information available about a company that has developed a similar machine learning algorithm for diagnosing opioid use disorders earlier.

In a separate development, researchers from MIT have developed a machine learning approach to predict the quality of biopharmaceutical products. This could potentially revolutionise the pharmaceutical industry by ensuring the production of high-quality, safe medicines.

On the topic of cancer detection, DeepHealth researchers have developed a deep learning model that can detect breast cancer one year earlier than standard clinical models. This breakthrough could significantly improve early detection rates and survival rates for breast cancer patients.

Amazon has also joined the fray by open-sourcing its Alexa technology, allowing companies to custom-build voice assistants. One such open-sourced technology is the Alexa Custom Assistant, which is being offered to automobile companies in 14 countries.

These advancements in machine learning and artificial intelligence are redefining the boundaries of healthcare and technology, offering hope for earlier diagnosis, improved prediction, and more accurate surveillance of various health conditions.