- Google Cloud recently launched new artificial intelligence 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 artificial intelligence tools, which includes the Healthcare Natural Language 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 in the back-office and in clinical practice,” Google officials said in a new official blog post.
Oftentimes, critical medical knowledge is stored in unstructured digital text, which means that it cannot be put into a standard database.
Google’s new Healthcare Natural Language API leverages natural language processing to help end-users coordinate medical insights that are captured in unstructured texts, including rates of vaccinations and medication adherence.
The Healthcare Natural Language API normalizes medical information against industry-standard knowledge. For example, diabetes is often referred to as diabetes mellitus in specialist terms.
With the new solution, similar medical information gets normalized into a standardized medical knowledge graph, Google explained.
Telehealth companies can leverage this solution to identify relevant symptoms, pre-existing conditions, and medications from a doctor-patient conversation, while pharmaceutical companies can use the solution to boost the accuracy of individual patient criteria.
Additionally, the machine learning approach helps to discern medications prescribed to patients in the past, from medications prescribed in the future, and identifies specific symptoms or diagnosis.
The machining learning component can also distinguish medical insights that concern the individual patient from information that pertains to his family member.
In addition to the Healthcare Natural Language API, Google also launched AutoML Entity Extraction for Healthcare.
This solution increases access to artificial intelligence across all users and allows healthcare professionals to build 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, such as vaccinations or medications, that may 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.”
In turn, operational spending is decreased and there is an improvement in the patient-doctor experience.
To successfully implement these two solutions, Google stated that it will 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 typically not found within the structured fields of a medical record system. Instead, it is contained within the lengthy free-text notes that a clinician either types or dictates into the medical record in the course of care,” said Michael Ames, Sr., director healthcare and life sciences at SADA. “I'm very excited for the opportunities this suite of Healthcare Natural Language AI tools from Google Cloud will create.”
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