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Microsoft releases Azure update with text analytics for health capabilities



Last updated 23/07/2021

Microsoft releases Azure update with text analytics for health capabilities

Microsoft on Wednesday reported the consideration of text analytics abilities inside its Azure Cognitive Services item. 

As per the product mammoth, the Text Analytics for health highlight can process a wide assortment of information types and assignments, including extricating in excess of 100 kinds of by and by recognizable data (counting ensured wellbeing data) from unstructured content. 

The new review highlight can likewise relate words or expressions in text with semantic elements –, for example, disease side effects; determination; medicine name and class; and measurement – and distinguish associations between ideas.

"Trained on a diverse range of medical data – covering various formats of clinical notes, clinical trials protocols, and more – the health feature is capable of processing a broad range of data types and tasks, without the need for time-intensive, manual development of custom models to extract insights from the data," said Hadas Bitran, Microsoft Healthcare group manager, in a blog after this announcement was spread out loud.



As indicated by Microsoft, Text Analytics for health can support suppliers, organizations, and analysts to build experiences and associations from unstructured English-language clinical information. The product additionally bolsters the location of modifiers like invalidation –, for example, when notes notice that a patient has not been determined to have something.

"Text Analytics for health enables researchers, data analysts, medical professionals and [independent software vendors] in the healthcare and biomedical space to unlock a wide range of scenarios – like producing analytics on historical medical data and creating prediction models, matching patients to clinical trials, or assisting in clinical quality reviews," said Bitran.

As one model, Bitran noted, Microsoft utilized Text Analytics alongside the organization's Cognitive Search to build up the COVID-19 internet searcher. The device permits scientists to look through in excess of 47,000 academic articles for pertinent data in the midst of the occasionally overpowering measure of substance with respect to the novel coronavirus.

Liam Cavanagh, Azure Cognitive Search team principal program manager, explained in an accompanying video, "We took a set of open data sets provided by the Semantic Scholar," part of the Allen Institute for AI, providing up-to-date research papers. 

TA for health, Cavanagh continued, "allows us to extract out all the important medical entities …that are discussed within that content and then tag it." 

"We wanted to make it so that you could really find what you're looking for," Cavanagh said, "so that even if you search for a very specific term, we wanted to use some AI capabilities ... based on what we know of that content, here are some other terms you could consider using to find more relevant information."


Other significant software farms have pinpointed the benefits of utilizing man-made reasoning to separate data from unstructured content, particularly where social insurance information is concerned. 

In late 2018, Amazon Web Services declared the dispatch of its Amazon Comprehend Medical, a HIPAA-qualified instrument to help process unstructured information and recognize persistent data.

"The process of developing clinical trials and connecting them with the right patients requires research teams to sift through and label mountains of unstructured medical record data," said Fred Hutchinson Cancer Research Center chief information officer Matthew Trunnell.

In the meantime, not long ago, SAS delivered its own COVID-19 pursuit instrument, which can extricate text and numerical information from in excess of 50,000 exploration articles and permit clients fast access to applicable data.



"The healthcare industry is overwhelmed with data. Much of this healthcare data is in the form of unstructured text, such as doctor’s notes, medical publications, electronic health records, clinical trials protocols, medical encounter transcripts and more," said Bitran.

"Healthcare organizations, providers, researchers, pharmaceutical companies, and others face an incredible challenge in trying to identify and draw insights from all that information. Unlocking insights from this data has massive potential for improving healthcare services and patient outcomes," Bitran continued.

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