|Babylon Health, of London||Artificial Intelligence (AI)-based symptom checker tool||Uses causal machine learning||Help doctors improve diagnosis||Published research in Nature Communications showing that disentangling correlation from causation makes AI significantly more accurate in diagnosing patients based on symptoms; a pool of over 20 Babylon general practitioners (GPs) created 1,671 realistic written medical cases; a separate group of 44 Babylon GPs were then each given at least 50 written cases (the mean was 159) to assess; the doctors listed the illnesses they considered most likely; Babylon's AI took the same tests and used both an older algorithm based on correlations (created specifically for this research) and the newer, causal one; the doctors had a mean score of 71.40% (± 3.01%) and ranged from 50-90%; the older correlative algorithm performed on par with the average doctor, achieving 72.52% (± 2.97%); the new causal algorithm scored 77.26% (± 2.79%), which was higher than 32 of the doctors, equal to 1, and lower than 11|
|Beyond Air Inc., of Garden City, N.Y.||Lungfit||Nitric oxide (NO) generator and delivery system||Treats pulmonary Mycobacterium abscessus disease||Study evaluated the effect of inhaled NO therapy delivered via the Lungfit system, with inhaled NO doses titrated up to 240 ppm, as compassionate treatment in a 24-year-old, female cystic fibrosis patient with chronic and progressive pulmonary M. abscessus disease; the patient completed the first 3-week treatment course with no significant adverse effects noted; in general, the patient noted improved respiratory symptoms and quality of life and had small improvements in her lung function, 6-minute walk distance, and inflammatory markers but no significant change in tests and cultures for M. abscessus; given the overall tolerability of the first treatment, the patient requested to repeat the treatment, but dosing was stopped after day 8 due to adverse symptoms, which did not occur during administration of NO, and methemoglobin levels remained within safe thresholds at all times; in vitro susceptibility tests showed a dose-dependent NO effect on M. abscessus susceptibility and significant heterogeneity in response among M. abscessus clinical isolates; the patient's isolate was found to be the least susceptible strain in vitro; the research was published in Access Microbiology|
|Exthera Medical Corp., of Martinez, Calif.||Seraph 100||Extracorporeal blood filter||For the reduction of pathogens in blood||Published case study in Critical Care Explorations in which the U.S. Department of Defense used the Seraph 100 to treat COVID-19; researchers at the Walter Reed Army Medical Center determined that the Seraph 100 may improve patient stability in COVID-19 cases requiring mechanical ventilation and vasopressor support; during and after the treatment with the Seraph 100, both patients experienced quantitative clinical improvement, and there were no device-related adverse events|
|Neurologica Corp., a Danvers, Mass-based subsidiary of Samsung Electronics Co. Ltd.||GM85 mobile DR system with S-Vue Image Engine||Mobile digital radiography (DR) system with a noise-reduction algorithm||Imaging of patients in the neonatal intensive care unit||A study in the American Journal of Roentgenology shows that low-dose protocols using the GM85 can deliver comparable image quality at up to a 36% lower dose; 40 neonatal patients underwent whole-body radiography with the GM85 protocol and a conventional protocol on another conventional mobile DR system; results showed that the low-dose protocols of both 80% and 64% equivalent dose "were statistically noninferior to the conventional protocol with respect to overall image quality," and the 80% dose had better overall image quality than the conventional protocol|
For more information about individual companies and/or products, see Cortellis.