Amazon’s new machine learning tool to decode unstructured medical data

Amazon has launched a new machine learning platform capable of extracting relevant medical data from unstructured text.

Amazon Comprehend Medical can read clinical notes, prescriptions and audio transcripts and identify clinical information buried within them.

It does this through what Amazon terms medical language processing, a form of natural language processing that can “identify medical conditions, anatomic terms, medications, details of medical tests, treatments and procedures,” without the need to first train the system or apply “large numbers of custom rules”.

It is hoped Amazon Comprehend Medical will enable healthcare providers, suppliers and researchers make better sense of large swatches of unstructured medical data, ultimately helping support clinical decision-making, medical trials and population health initiatives.

“The majority of health and patient data is stored today as unstructured medical text, such as medical notes, prescriptions, audio interview transcripts, and pathology and radiology reports,” a post on Amazon’s machine learning blog read.

“Identifying this information today is a manual and time-consuming process, which either requires data entry by high skilled medical experts, or teams of developers writing custom code and rules to try and extract the information automatically.

“Ultimately, this richness of information may be able to one day help consumers with managing their own health, including medication management, proactively scheduling care visits, or empowering them to make informed decisions about their health and eligibility.”

Amazon is working with the Fred Hutchinson Cancer Research Centre in Seattle, where Comprehend Medical is being used in medical trials to identify patients who may benefit from specific cancer therapies.

According to the tech firm, the platform has enabled the hospital to rapidly extract and index medical conditions, medications, and choice of cancer therapeutic options from millions of clinical notes.

Matthew Trunnell, CIO of Fred Hutchinson Cancer Research Center, said: “For cancer patients and the researchers dedicated to curing them, time is the limiting resource. 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.

“Amazon Comprehend Medical will reduce this time burden from hours per record to seconds. This is a vital step toward getting researchers rapid access to the information they need when they need it so they can find actionable insights to advance lifesaving therapies for patients.”

Another AWS customer that has previewed the service is Roche Diagnostics.

Anish Kejariwal, the company’s director of software engineering for information solutions, said: “With petabytes of unstructured data being generated in hospital systems every day, our goal is to take this information and convert it into useful insights that can be efficiently accessed and understood

“Amazon Comprehend Medical provides the functionality to help us with quickly extracting and structuring information from medical documents, so that we can build a comprehensive, longitudinal view of patients, and enable both decision support and population analytics.”