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AI Announces Successful Results from its Burn Validation Study of the DeepView System
DeepView System outperforms burn physicians in identifying non-healing tissue
Landmark Burn Validation Study, one of the largest in U.S. history, confirms DeepView's performance
Spectral AI plans FDA submission by mid-2025, targeting De Novo Clearance and rapid commercialization to transform burn care
TX - March 17, 2025 (GLOBE NEWSWIRE) -- Spectral AI (NASDAQ: MDAI) ("Spectral AI" or the "Company"),
developer of the AI-driven DeepView System, that uses multi-spectral imaging and AI algorithms to predict burn healing potential,announced
the successful results of the performance of its DeepView System in connection with the completion of its Burn Validation Study. Spectral
AI's DeepView System is being developed as a predictive device to offer clinicians an immediate and objective assessment of a burn
wound's healing potential prior to treatment or other medical intervention. The image processing algorithm employed by the DeepView
System utilizes multispectral imaging that is trained and tested against a proprietary database of more than 340 billion clinically validated
data points. The DeepView System is non-invasive and cart-based, allowing for exceptional mobility within the healthcare setting.
Burn Validation Study, which began in January 2024 and concluded in March 2025, represented one of the largest burn trials ever conducted
in the United States. The Company enrolled and analyzed data obtained from 164 total patients comprised of 115 adult and 49 pediatric
patients in burn centers and emergency departments across the U. S. in its Burn Validation Study. The goal of the Burn Validation Study
was to further demonstrate the innovative and versatile nature of Spectral AI's DeepView technology, as well as its ability to
predict burn wound healing potential on the first day of injury with greater performance and speed than the methods currently used today.
The Burn Validation Study results, together with rigorous statistical analysis, illustrate that the DeepView System continues to outperform
the clinical judgment of burn physicians by a large margin.
Burn Validation Study results assessed the sensitivity, specificity and Dice score of the DeepView System at both a pixel-level and image-wise
level against the clinical judgment of burn physicians. Key findings included the following:
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believe these are excellent results and we are thrilled with the analysis of our DeepView System in our Burn Validation Study,"
said Dr J. Michael DiMaio, M.D. "The DeepView System exceeded our expectations in terms of predictive performance. Following the
FDA's review, if authorized by the agency, our hope is that this tool will provide an objective and immediate prediction of non-healing
burn tissue to expedite patient care and reduce system costs across the board. I would like to thank Jeffrey C. Carter, MD, FACS, the
principal investigator for the Burn Validation Study, our entire team at Spectral AI, and especially the patients and esteemed clinicians
who participated in this Study. We look forward to bringing this predictive diagnostic tool to the United States marketplace as soon
AI plans to submit these results to the FDA as part of its regulatory submission by the end of the second quarter of 2025 and hopes to
have the FDA grant the De Novo Classification Request of the DeepView System in early 2026. Based on its current manufacturing arrangements,
Spectral AI will be prepared to commercialize the DeepView System in the United States, if ultimately approved, as soon as approval is
project is being supported in whole or in part with federal funds from the Department of Health and Human Services; Administration for
Strategic Preparedness and Response; BARDA, under contract number 75A50123C00049.
AI, Inc. is a Dallas-based predictive AI company focused on medical diagnostics for faster and more accurate treatment decisions in wound
care, with initial applications involving patients with burns. The Company is working to revolutionize the management of wound care by
"Seeing the Unknown " with its DeepView System. The DeepView System is being developed as a predictive device
to offer clinicians an objective and immediate assessment of a burn wound's healing potential prior to treatment or other medical
intervention. With algorithm-driven results and a goal of exceeding the current standard of care in the future, the DeepView System
is expected to provide fast and accurate treatment insight towards value care by improving patient outcomes and reducing healthcare costs.
For more information about the DeepView System, visit www.spectral-ai.com.
statements made in this release are "forward looking statements" within the meaning of the "safe harbor" provisions
of the United States Private Securities Litigation Reform Act of 1995, including statements regarding the Company's strategy, plans,
objectives, initiatives and financial outlook. When used in this press release, the words "estimates," "projected,"
"expects," "anticipates," "forecasts," "plans," "intends," "believes,"
"seeks," "may," "will," "should," "future," "propose" and variations
of these words or similar expressions (or the negative versions of such words or expressions) are intended to identify forward-looking
statements. These forward-looking statements are not guarantees of future performance, conditions or results, and involve a number of
known and unknown risks, uncertainties, assumptions and other important factors, many of which are outside Company's control, that
could cause actual results or outcomes to differ materially from those discussed in the forward-looking statements. As such, readers
are cautioned not to place undue reliance on any forward-looking statements.
should carefully consider the foregoing factors, and the other risks and uncertainties described in the "Risk Factors" sections
of the Company's filings with the SEC, including the Registration Statement and the other documents filed by the Company. These
filings identify and address other important risks and uncertainties that could cause actual events and results to differ materially
from those contained in the forward-looking statements.
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