Google Cloud recently launched new AI tools for healthcare users intended to combat challenges with healthcare data and unstructured digital text during the COVID-19 pandemic.

The suite of fully-managed AI tools, which incorporates the Healthcare tongue API and AutoML Entity Extraction for Healthcare, will assist healthcare professionals with reviewing and analyzing large volumes of medication documents.

We hope this technology will help reduce workforce burnout and increase healthcare productivity, both within the back-office and in clinical practice,” Google officials said during a new official blog post.

Oftentimes, critical medical knowledge is stored in unstructured digital text, which suggests that it can’t be put into a typical database.

Google’s new Healthcare tongue API leverages tongue processing to assist end-users coordinate medical insights that are captured in unstructured texts, including rates of vaccinations and drugs adherence.

With the new solution, similar medical information gets normalized into a uniform medical knowledge graph, Google explained.

Telehealth companies can leverage this solution to spot relevant symptoms, pre-existing conditions, and medications from a doctor-patient conversation, while pharmaceutical companies can use the answer to spice up the accuracy of individual patient criteria. Additionally, the machine learning approach helps to discern medications prescribed to patients within the past, from medications prescribed within the future, and identifies specific symptoms or diagnosis.

The machining learning component also can distinguish medical insights that concern the individual patient from information that pertains to his loved one. In addition to the Healthcare tongue API, Google also launched AutoML Entity Extraction for Healthcare.

This solution increases access to AI across all users and allows healthcare professionals to create their own tools for extracting important information from digital documents.

Through a low-code interface, professionals can build tools for gene mutations and socioeconomic factors, Google said. AutoML Entity Extraction for Healthcare also enhances digital health applications, including telemedicine, drug discovery, or clinical trials for rare diseases.

“Patients can better coordinate valuable medical insights that are captured in unstructured texts, like vaccinations or medications, which will be overlooked as patients move through their healthcare journeys,” Google said.

“This solution can drive measurable outcomes by lowering the likelihood of redundant bloodwork or other tests, reducing operational spending, and improving the patient-doctor experience.” To successfully implement these two solutions, Google stated that it’ll partner with various key solution providers.

Google Cloud solutions provider, SADA, said that the new tools will help healthcare customers implement medical analysis projects in days.

“The richest information about the health of a patient is usually not found within the structured fields of a medical history system. Instead, it’s contained within the lengthy free-text notes that a clinician either types or dictates into the medical history within the course of care.

By Joseph

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