Anosmia to amyloidosis: nference’s AI is decoding healthcare data at scale

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The complexity of patient records, with their mix of unstructured notes and diverse data types, defies traditional analysis. While a thorough review of even a single patient’s file can be tedious  for a human, AI tools offer the power to analyze tens or even hundreds of millions of records, unlocking data patterns that would otherwise remain hidden.

A burgeoning number of companies are popping up to address the tasks of amalgamating and deciphering patient records using AI tools. Among them is nference, which has attracted backing of notable institutions such as the Mayo Clinic, Duke Health, Emory Healthcare, Vanderbilt University Medical Center and The Bill & Melinda Gates Foundation. In 2020, the company was highlighted as one of the top digital startups in the world.

Nference’s AI platform has a vast array of data at its disposal. In all, it captures more 11 million patien…

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Anumana wins FDA clearance for ECG-AI algorithm

Screen shot of sample data from Anumana’s ECG-AI LEF. [Image courtesy of Anumana]Anumana announced that it received FDA 510(k) clearance for its AI-powered ECG-AI LEF medical device.

Cambridge, Massachusetts-based Anumana, an Nference portfolio company, worked in collaboration with Mayo Clinic. They designed the breakthrough medical device to detect low ejection fraction (LEF) in patients at risk of heart failure. The company’s pulmonary hypertension (PH) early detection algorithm also won FDA breakthrough device designation last year.

Developed as software-as-a-medical device (SaMD), the algorithm screens LEF in adults at risk for heart failure. It uses data from a routine 12-lead electrocardiogram (ECG). Anumana developed it using research from Mayo Clinic that included more than 100,000 ECG and echocardiogram data pairs. The data came from more than 25 studies evaluating more than 40,000 patients in the U.S. and abroad.

Further data from 16,0…

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Anumana wins FDA breakthrough nod for AI algorithm that detects pulmonary hypertension

Anumana announced today that it received FDA breakthrough device designation for its pulmonary hypertension (PH) early detection algorithm.

Cambridge, Massachusetts-based Anumana, formed by Mayo Clinic and nference and launched in 2021, designed its AI-enhanced, electrocardiograph (ECG)-based PH early detection algorithm as a precise, non-invasive screening tool to provide earlier diagnosis for patients with PH that may otherwise go unnoticed until the disease has advanced.

The algorithm leverages 12-lead ECGs and is enabled by the nference platform that provides insight from more than 6 million de-identified patient records, including over 8 million ECGs. It analyzes the voltage-time data and within seconds provides a prediction of the likelihood of PH, reducing the time between initial symptoms and the first evaluation for PH via targeted cardiac imaging.

According to a news release, the algorithm was developed through a collaboration between data scie…

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Making biomedical data computable

Vik Nagjee is the vice president of product at nference [Photo courtesy of nference]

Cloud computing can power quantum leaps in human health.

Vik Nagjee, nference

A state-of-the art platform that supports real world evidence (RWE) and health economics and outcomes research can enable breakthroughs at an unprecedented scale.

This is achieved by making the de-identified, transformed information contained within the electronic medical record (EMR) available for data science and analysis at the aggregate and patient level. Add multi-modal data sources such as imaging and electrocardiograms as well as novel data assets like digital pathology and omics data to enrich the EMR data to provide a truly longitudinal view of the patient, and you have the beginnings of a world-class platform.

The keys are privacy preservation, harnessing longitudinal data, data enrichment and a data science platform.

P…
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Mayo Clinic helps launch two new companies for improved diagnostics

Mayo Clinic announced that it is introducing a new technology platform to support two new companies it has launched.

Rochester, Minn.–based Mayo Clinic’s Remote Diagnostics & Management Platform (RDMP) is designed to connect data with new AI algorithms and augment human decision-making within existing clinical workflows, according to a news release.

“The dramatically increased use of remote patient telemetry devices coupled with the rapidly accelerating development of AI and machine learning algorithms has the potential to revolutionize diagnostic medicine,” Mayo Clinic Platform president Dr. John Halamka said in the release. “With RDMP, clinicians will have access to best-in-class algorithms and care protocols and will be able to serve more patients effectively in remote care settings. The platform will also enable patients to take more control of their health and make better decisions based on insights delivered directly to them.”

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The top digital health startups in the world

About two-fifths of the startups in CB Insights’ second annual Digital Health 150 list are engaged in telehealth, a high-demand area amid the COVID-19 pandemic.

That is one of the big takeaways from the list of 150 promising digital health startups that CB Insights released today. CB Insights’ research team picked the 150 startups after using the company’s platform to evaluate nearly 8,000 startups on factors including patent activity, business relations, investor profile, news sentiment analysis, proprietary Mosaic scores, market potential, competitive landscape, team strength and tech novelty. (Download the full report here.)

The 62 telehealth startups on the list include telemedicine platforms such as cardiology platform Heartbeat Health (New York), virtual visit platform Doctor On Demand (San Francisco), and Livi medical app creator KRY (Stockholm, Sweden). There are remote monitoring and diagnostics companies including Oura (Oulu, Finland…

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