DALLAS, June 10, 2025 (GLOBE NEWSWIRE) -- Spectral AI, Inc. (Nasdaq: MDAI) (“Spectral AI” or the “Company”), an artificial intelligence (AI) company focused on medical diagnostics for faster and more accurate treatment decisions in wound care, today announced its prominent role at the annual British Burn Association (BBA) conference, held from June 4^th – 6^th in Brighton, UK. The Company was featured in multiple presentations, highlighting its contributions to advancing burn care across the globe.

Key Presentations at BBA:

• The First Reader Study of Burn Wounds with Predictive Artificial Intelligence Analysis – Dr. Jeffrey Carter, M.D., Louisiana State University Health Science Center
• Artificial Intelligence-Enhanced Multispectral Imaging for Burn Wound Assessment: Insights from a Multi-Centre UK Trial – Leslie Poh Hong Tan, Royal Victoria Infirmary
• Can artificial intelligence see beyond what the human eyes see? ‘A prospective study to assess the accuracy of the DeepView Snapshot system in predicting wound healing potential’ – Suhaila Abouhadid, North Bristol NHS Trust
• Patient experience of artificial intelligence: is the use of a multispectral imaging device as part of a burns consultation acceptable to patients? – Miriam Nyeko-Lacek, Manchester University NHS Foundation Trust
  
  

Among the key presentations, Mr. Chris Wearn, MBiochec (Hons), PhD, FRCS (Plast), clinical lead at the Bristol Adult Burns Service and the South-West UK Children’s Burns Centre based at Bristol Royal Children’s Hospital shared his experience with the DeepView^® System. His presentation at the Spectral AI Symposium, titled “DeepView Snapshot: Early experience in the Bristol Adults Burn Service” highlighted the potential value of the DeepView System in supporting the delivery of burn care in a UK hospital.

"Our early experience has demonstrated that DeepView could significantly improve acute burn care. The device’s portability and ease of use allows all members of the team to scan patients on admission.  The rapidly generated AI driven healing prediction tool supports our clinical decision making when determining the best treatment for our patients. We are excited about these early positive experiences and what this means for the future of burn care," said Mr. Chris Wearn.

Dr. Jeffrey Carter added, “UK investigators shared valuable advancements with DeepView during the BBA meeting. Their early clinical experience demonstrated promising sensitivity and specificity results, along with a positive patient experience and a comprehensive evaluation of TBSA (Total Body Surface Area) calculation methods. In addition, we presented findings from a reader study — a structured research methodology used to evaluate emerging imaging technologies — which showed that DeepView significantly improved clinicians' ability to detect non-healing wounds, increasing detection rates from 61% to 89% (p < 0.0001)."

The British Burn Association Conference is a premier event that brings together leading clinicians, researchers, and innovators in burn care. The Company’s participation and presence in multiple sessions underscores its commitment to driving advancements in the field and supporting healthcare professionals in delivering better outcomes for burn patients.

Dr. J. Michael DiMaio, M.D., Chairman of the Board of Spectral AI, expressed pride in the Company’s role at the conference: "It’s an honor to see our Company featured so prominently at the British Burn Association Conference this year. Our mission is to empower clinicians with the advanced technology they need to transform patient care. The feedback from clinicians reinforces the impact we’re making, and we’re excited to continue innovating for the future of burn treatment."

About Spectral AI
Spectral 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.

Forward-Looking Statements
Certain 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. 

Investors 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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