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Source: MDDI
Condition: Heart Failure
Education: Learning
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Total 3 results found since Jan 2013.
Developing a New Score: How Machine Learning Improves Risk Prediction
Composite risk scores have been used for decades to identify disease risk and health status in the general population. However, current approaches often fail to identify people who would benefit from intervention or recommend unnecessary intervention. Machine learning promises to improve accuracy, ensuring targeted treatment for patients that need it and reducing unnecessary intervention.
Framingham Risk Score, the gold standard for predicting the likelihood of heart disease, predicts hospitalizations with about 56% accuracy. It uses factors such as age, gender, smoking, cholesterol levels, and systolic blood pressure to...
Source: MDDI - November 17, 2017 Category: Medical Devices Authors: Heather R. Johnson Tags: R & D Source Type: news
Published Study Supports MyoKardia ’s Wrist-Worn Biosensor
MyoKardia’s said data on its wrist-worn digital health device was published in an article titled, “Machine Learning Detection of Obstructive Hypertrophic Cardiomyopathy (oHCM) Using a Wearable Biosensor,†in the Nature Partner Journal, Digital Medicine.
The South San Francisco-based company said results from an exploratory study provided encouraging evidence of the potential for a wrist-worn biosensor to screen for obstructive hypertrophic cardiomyopathy.
The study demonstrated that continuous monitoring using a wrist-worn photoplethysmography (PPG) digital health devic...
Source: MDDI - June 24, 2019 Category: Medical Devices Authors: MDDI Staff Tags: Business Cardiovascular Source Type: news
What ’s the Big Deal about Data in Medtech?
Discussion, “Top 5 Things You Need to Know about the Implantable Internet of Things."
Brian Chapman, partner and leader of ZS’s medtech practice of ZS, attributes today’s focus on data to the intersection of two important things:
"A general recognition that understanding more and connecting actions with outcomes will provide feedback and understanding that will drive standards of care. This is not new, but as capabilities rise in data collection, aggregation, and synthesize rise, and coupled with machine learning, the promise of data in healthcare is becoming even more ...
Source: MDDI - December 20, 2019 Category: Medical Devices Authors: Daphne Allen Tags: Digital Health Source Type: news
