The Nevisense Go, a portable, non-invasive tool that uses electrical impedance spectroscopy to assess the skin barrier, will be studied in clinical practice in a Swiss hospital.
Why it matters
Atopic dermatitis affects 20% of children, SciBase, developers of AI technology say the ability to predict who is at risk for such eczema before it develops could significantly expand treatment – potentially preventing the disease and The underlying disease may persist into adulthood.
The Swedish company developing augmented intelligence-based solutions for dermatology announced a two-year partnership with Johnson & Johnson. The study is a validation test of how SciBase’s portable, non-invasive tool can help predict atopic dermatitis in infants.
SciBase CEO Simon Grant said in a video accompanying the announcement. According to the SciBase website, in allergies and autoimmune diseases worldwide.
“I deal with different allergic diseases in children every day, which is a growing problem,” lead study investigator Caroline Roduit, MD, said in the announcement.
“Allergic diseases have a natural progression, with atopic dermatitis appearing first, usually already in infancy, followed by other allergic diseases such as food allergies and anaphylaxis asthma,” she said. “The ability to identify these children early will help in the development of prevention strategies for allergic diseases,” she explained.
Skin barrier assessment is a newer application of SciBase’s EIS technology, which has been used in the US and EU for the detection of melanoma and non-melanoma skin cancers.
In 2020, SciBase announced that Nevisense would be used to measure skin properties, including barrier function, a study from the Mount Sinai Pediatric Allergy Unit looked at how birth type affects the risk of developing skin allergies.
Grant said that once developed, the solution could be used for postpartum care for clinicians and home monitoring for parents.
Megatrend
Using AI to Predict Patient Conditions is an Evolving Collaboration and development areas.
An algorithm was able to predict oxygen levels in COVID-19 patients with more than 88% specificity, according to a study published last year involving data from more than 20 hospitals around the world.
Combining AI with precision medicine can also enable personalized diagnosis, an area where significant investments are being made in healthcare technology.
At Sanford Health in Sioux Falls, South Dakota, using machine learning to analyze data and identify patients who could benefit from proactive treatments is a priority, says chief operating officer Matt Hocks.
“Precision medicine will allow us to focus on prevention and early screening, diagnosis and care that will help keep our patients healthy and prosperous for generations to come,” He told Healthcare IT News when discussing health IT investments.
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“The promise of this test is that it is non-invasive is available and widely available — in this study, testing will be performed in the infant’s home using the Nevisense Go,” Grant said in the announcement. “We see this collaboration as an important step in shaping the future of medical technology accessibility, non-invasiveness, and personalization.”
Andrea Fox Senior Healthcare IT News editor. Email: [email protected] Healthcare IT News is a HIMSS publication.
