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DeepView AI System

by Spectral AI, Inc. (formerly Spectral MD, Inc.) · Based in United States → — Seeing the Unknown® with its DeepView System

Dermatology Emergency Medicine Plastic Surgery

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Overview

The DeepView AI System is an AI-based wound assessment and imaging platform developed by Spectral AI. It is designed to support non-invasive, real-time burn wound evaluation, using advanced multispectral imaging and deep learning to deliver objective predictions of wound healing potential. This allows healthcare providers to make faster, more informed treatment decisions without the need for invasive diagnostics like biopsies. The system provides an immediate, data-driven assessment of whether areas within burn wounds are unlikely to heal within 21 days and may require significant medical intervention. The image acquisition takes 0.2 seconds, and all image processing and AI model classification takes approximately 20 to 25 seconds. The DeepView System is trained and tested against a proprietary and clinically validated database of over 340 billion pixels of burn wound image data.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

Non-invasive, real-time burn wound evaluation
Advanced multispectral imaging
Deep learning and proprietary AI algorithms for wound healing prediction
Objective predictions of wound healing potential
Immediate, data-driven assessment (within 20-25 seconds)
Predicts if a wound is unlikely to heal within 21 days
Trained on a proprietary, clinically validated database of over 340 billion pixels of burn wound image data
Non-contact, painless, radiation-free imaging technique
Option for EHR connectivity
Portable and designed for various healthcare settings (burn centers, trauma units, emergency departments)

Use Cases

Burn wound assessment and treatment decisions
Early assessment in burn centers, trauma units, and emergency departments
Predicting healing potential of thermal burn wounds
Identifying burn wounds that may require surgical intervention
Diabetic foot ulcer healing assessment
Medical countermeasure for burn mass casualty incidents

What Physicians Need to Know

Evidence Base

The DeepView AI System's AI algorithm was trained and tested using a proprietary, clinically validated burn wound database containing over 340 billion data points. This extensive dataset was collected through clinical studies, including Spectral AI's U.S. pivotal burn study, which involved sequential imaging of burn wounds up to the point of surgery or 21 days post-injury.

Clinical Validation Studies

A pivotal U.S. burn study demonstrated that the DeepView AI System consistently predicted burn wound healing potential, outperforming traditional clinical judgment. The Burn Validation Study, one of the largest in U.S. history, included 164 patients (115 adult and 49 pediatric) across U.S. burn centers and emergency departments. Key findings showed the DeepView System had an image-wise sensitivity of 86.6% in identifying non-healing tissue, compared to 40.8% for burn physicians' clinical judgment. Pixel-wise sensitivity was 81.9% for DeepView versus 38.8% for physicians. The system also achieved a statistically significant higher Dice Score of 68.5% compared to 39.2% for physicians, indicating improved pixel-wise evaluation. While physicians had higher image-wise specificity (79.1% vs. 61.2%), this was attributed to their conservative assessment of burn areas. In a multi-center UK trial, the DeepView technology showed over 95% overall accuracy in predicting healing potential in a burn wound by 21 days.

Clinical Workflow Integration

The DeepView AI System is designed to integrate with existing electronic health records (EHRs) and clinical workflows. It is a non-invasive, cart-based system, allowing for mobility within healthcare settings. The image acquisition takes 0.2 seconds, and the AI analysis and classification take approximately 20-25 seconds, providing rapid diagnostic insights. The system provides an immediate, data-driven assessment to aid in earlier and more informed treatment decisions.

Physician Tip

The DeepView AI System is an adjunctive diagnostic tool and should be used in conjunction with clinical assessment, not as a standalone diagnostic device. It provides objective, standardized insights into burn wound healing potential, which can help reduce variability in assessments, especially within the critical first 24-48 hours post-injury. The rapid assessment (image acquisition in 0.2 seconds, AI analysis in 20-25 seconds) can facilitate faster, more informed treatment decisions and potentially streamline burn center workflows. The system highlights areas unlikely to heal within 21 days, aiding in prioritizing treatment and potentially reducing unnecessary procedures.

The DeepView AI System is being designed for integration with electronic health records (EHRs) and existing clinical workflows to seamlessly incorporate wound imaging and healing predictions into patient treatment plans.

At a glance

Deployment On Premise (device Based)

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Details

Category	Clinical Decision Support & Reference, Dermatology AI, Radiology & Imaging AI
Pricing	Unknown Estimated annual cost per site: ~$50,000–$100,000 (device + subscription); Device Cost: ~$30,000–$50,000 annually per site (lease/subscription, covering hardware, support, and maintenance); Subscription Costs (AI/Database Updates): ~$20,000–$50,000 annually per site (AI algorithms, burn database access, and software enhancements)
Deployment	On-premise (device-based)
Compliance
BAA Available	Unknown AI-estimated
HIPAA Compliant	Unknown AI-estimated
FDA Status	Unknown AI-estimated The DeepView System received De Novo clearance from the U.S. Food and Drug Administration (FDA) in May 2026, authorizing commercial distribution in the United States. It was also designated as a Breakthrough Device by the FDA in 2018 for its burn indication.
Integrations
EHR	Not specified
Specialties	Dermatology, Emergency Medicine, Plastic Surgery

What the Web Says

The DeepView AI System, developed by Spectral AI, is an AI-based wound assessment and imaging platform designed to provide objective, real-time predictions of wound healing potential for burn wounds and diabetic foot ulcers (DFUs). It utilizes multispectral imaging and deep learning to analyze tissue viability, aiming to improve diagnostic accuracy and streamline treatment decisions. The system has demonstrated high accuracy rates, with 92% for burn wounds in adults and 88% for pediatric burns, and 86% for DFUs. The DeepView AI System received De Novo authorization from the FDA in May 2026 for burn wound assessment.

Overall: Positive

Strengths

Provides objective and standardized insights into wound healing potential, reducing variability in clinical assessments.
Offers faster and more informed treatment decisions, potentially reducing hospital stays and costs.
Demonstrates high accuracy in assessing burn wounds (92% for adults, 88% for pediatric) and DFUs (86%).
Non-invasive, requiring only a single image for assessment.
Designed to integrate with existing electronic health records (EHRs) and clinical workflows.
Aims to reduce unnecessary patient transfers and optimize resource utilization in burn care.

Limitations

Some general concerns exist regarding AI in healthcare causing physician deskilling, though not specifically tied to DeepView AI.
As of early 2026, only a small percentage of FDA-cleared AI/ML devices had been evaluated for patient-centered outcomes like mortality or readmissions.
Reddit discussions on healthcare IT upgrades show mixed opinions on the value of new digital systems, with some citing wasteful spending.
The system is a prescription-only device.
No specific cons from G2 or Capterra reviews were found, suggesting limited public reviews on these platforms.
No specific cons from physicians or healthcare IT professionals were found in the search results, beyond general AI concerns.

Based on reviews from: Spectral AI, Inc. (MDAI) - Intro-act, DeepView AIu00ae System FAQs | Spectral AI for Burn Care Providers, Q2 2026 AI/ML FDA Clearances and De Novos - Innolitics, Spectral AI ($MDAI) is an astoundingly undervalued gem wrongfully priced for failure. An initial due diligence. : r/SpectralAI - Reddit, Military Medical AI and Deskilling: The Tourniquet Test - Jeremy Cleland, DeepView AI system for burn wound assessment at British Burn Association conference | Nottingham, England - Facebook, Publications - symplr, Michael Lynskey from our UK team was at the #IPSC2019 conference today talking about the Wound Care Sector Deal. By working with the NHS & harnessing digital Clinical Decision Support tools to reduce variation in treatment of wounds, we can help to improve outcomes by healing more wounds, more quickly and reducing dressing costs and nurse time. - Facebook, Regulatory Roundup Index Search - GitHub Pages, Spectral AI Stock Surges After Securing New Funding for FDA-Approved Imaging System

Last updated: 2026-09-24

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Press & Coverage

Innolitics

Q2 2026 AI/ML FDA Clearances and De Novos - Innolitics

SpectralMD received De Novo authorization (DEN250028) for the DeepView AI System in Q2 2026, which uses optical imaging and AI to assess burn tissue and predict healing within 21 days. The FDA required standalone performance, sensitivity, specificity, segmentation accuracy, subgroup analysis, and evidence of improved user diagnostic characterization.

2026-07

Binance Square (Cryptopolitan)

AI Can Help Diagnose Skin Burns More Accurately and Quickly | Cryptopolitan on Binance Square

The DeepView AI system, developed by Dallas-based Spectral AI, uses a specialized camera and AI software to identify permanently damaged skin from burns with 90% accuracy in seconds, significantly reducing the time for diagnosis compared to traditional methods. The system also focuses on diabetic foot ulcers.

2024-05

FDA

Breakthrough Devices Program - FDA

The DeepView AI System (DEN250028) received Breakthrough Device designation from the FDA on May 21, 2026. This program aims to accelerate the development and review of medical devices that provide more effective treatment or diagnosis for life-threatening or irreversibly debilitating diseases or conditions.

2026-08

Tim Sykes

Spectral AI Stock Surges After Securing New Funding for FDA-Approved Imaging System

Spectral AI received a $31.7 million increase in BARDA funding, bringing the total commitment to $54.9 million, to enhance the DeepView AI system's burn-wound imaging features as it approaches FDA market approval. This funding led to a significant surge in Spectral AI's stock value.

2026-03

symplr

DeepView AI System (Spectral AI Inc.) for Assessment of Burn Wounds

Symplr Evidence Analysis offers publications, including one on the DeepView AI System (Spectral AI Inc.) for the assessment of burn wounds, providing unbiased analyses on the clinical, financial, and risk impacts of emerging healthcare technologies.

unknown

GitHub Pages (MENASA Group)

Regulatory Roundup Index Search - GitHub Pages

The DeepView AI System is described as a prescription, software-aided adjunctive diagnostic device intended to assist healthcare providers in the clinical assessment and management of burn wounds.

2026-06

Gods in White

Die FDA erteilt eine De-Novo-Freigabe fu00fcr das DeepView-AI-System zur Wund- und Brandbeurteilung, ein regulatorischer Schritt fu00fcr KI in der klinischen Bildauswertung.

The FDA granted De Novo clearance for the DeepView AI System for wound and burn assessment on July 1, 2026, marking a significant regulatory step for AI in clinical image analysis.

2026-07

Alfabeta CRO

DeepView AI Systemu7372FDAu6838u51c6uff1aAI u8f14u52a9u71d2u50b7u50b7u53e3u8a55u4f30 - Alfabeta CRO

The DeepView AI System, developed by Spectral AI, Inc., received FDA marketing approval via the De Novo pathway on May 21, 2026. It is classified as a Class II medical device and is a software-aided adjunctive diagnostic device for skin wound assessment.

2026-07

Videos

Product demos, reviews, and walkthroughs for DeepView AI System.

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Frequently Asked Questions

How does the DeepView AI System assist in clinical decision-making for burn wounds?

The DeepView AI System is a non-invasive, predictive medical device that uses multispectral imaging and AI algorithms to assess the healing potential of burn wounds. It provides physicians with an immediate, data-driven assessment of whether areas within burn wounds are unlikely to heal within 21 days, aiding in earlier and more informed treatment decisions.

What is the FDA clearance status of the DeepView AI System?

The DeepView System received De Novo Classification from the U.S. Food and Drug Administration (FDA) in May 2026, authorizing Spectral AI to begin commercial distribution activities in the United States.

How accurate is the DeepView AI System compared to traditional clinical judgment?

In a pivotal U.S. burn study, the DeepView AI System demonstrated 86.6% sensitivity in predicting burn healing outcomes, significantly outperforming physicians' 40.8% accuracy in identifying non-healing tissue.

What are the potential limitations of the DeepView AI System?

The DeepView AI System is currently indicated for thermal burn wounds only, and its output should be used in conjunction with clinical judgment, not as a standalone diagnostic device. It does not provide definitive delineation of deep burn margins for precise excision sizing.

Are there any alternatives to the DeepView AI System for burn assessment?

Laser Doppler Imaging (LDI) is an established alternative that measures blood flow to predict burn outcomes, typically achieving 80-85% sensitivity. However, LDI devices are generally larger, less portable, and require trained operators, while DeepView offers a faster, more user-friendly, and portable solution.

What is the estimated cost of the DeepView AI System for a healthcare facility?

Based on industry benchmarks, the estimated annual cost for the DeepView System could range from $50,000 to $100,000 per site. This includes an estimated device cost of $30,000u2013$50,000 annually (lease/subscription) and an additional $20,000u2013$50,000 annually for AI algorithms and software updates.

Can the DeepView AI System integrate with existing hospital systems like EHRs?

The DeepView AI System is being designed to integrate with electronic health records (EHRs) and existing clinical workflows. This aims to facilitate the incorporation of wound imaging and healing predictions into daily patient treatment plans.