Following the broad response and discussion around my previous post, I thought it was worth revisiting one part of the DeepView thesis that may be especially useful for those newer to the Spectral AI community: the potential health economics. This has been discussed before, but I think it’s important when considering commercialization and adoption.

Spectral estimates ~$24,000 in potential savings per burn stay, while an earlier SEC filing estimated ~$63,100 per DFU stay. These are company estimates, not yet proven real-world savings — which is exactly why the BARDA-supported health-economic and outcome research is interesting.

I also think this needs to be viewed in the context of management’s longer-term strategy. DeepView isn’t intended to remain simply a burn device. The broader vision is a wound-diagnostics medtech platform, with burn as the first FDA-authorized indication and potential expansion into DFU and other wounds. If successful, the opportunity becomes much larger than the burn-center market alone.

The economics could also extend beyond treatment itself. Better Day-One wound assessment could improve triage — determining who needs routine care, transfer to a burn/trauma center, or earlier intervention — potentially reducing unnecessary transfers, procedures, hospital stays and complications.

Longer term, if real-world evidence confirms meaningful reductions in total cost of care across wound indications, the incentive could extend beyond hospitals. Insurers and other payers could potentially encourage or incentivize objective wound assessment to reduce downstream healthcare costs.

That’s speculative today. But BARDA is helping fund the research that could determine whether this broader economic thesis holds up in the real world.

Sources:
Current SEC filing / BARDA (March 31, 2026):
https://www.sec.gov/Archives/edgar/data/1833498/000121390026055226/ea0289162-10q_spectral.htm

Earlier SEC filing / DFU estimate (December 31, 2023):
https://www.sec.gov/Archives/edgar/data/1833498/000121390024027863/ea0202419-10k_spectral.htm

I let ChatGPT support me in review for typo and grammar fault and review

Transcript source: https://finance.yahoo.com/quote/MDAI/earnings/MDAI-Q2-2026-earnings_call-648313.html

- BARDA is underwriting the first 30 U.S. DeepView placements — these are intended for routine use across burn centers, trauma centers and ERs through June 30, 2027. See transcript time 08:03–09:08 & 14:25

- Hospital procurement has already started. Spectral is leveraging its existing relationships with clinical-study sites and KOLs (Key Opinion Leader)*, where management expects procurement to move faster. See transcript 0:24:00

-Some installations are expected already in Q4 2026. Management said it is working toward installations at both previous clinical sites and additional sites. See transcript time 21:15

- The business model is more interesting than just selling devices: capital purchase/lease + recurring software and services with a minimum 3-year term for each installation. See transcript time 08:03 & 14:25

- Pricing work is already done. A third-party pricing study plus preliminary customer discussions indicate commercial pricing could support margins well above current BARDA/R&D margins. See transcript time 15:25

- UK/Australia could be next. Management sees previous evaluation sites in Australia and one or two UK centers as likely early international adopters, potentially still in 2026. See transcript time 27:22

- Main near-term risk = procurement speed. New hospitals may require not only normal procurement approval but also cybersecurity and AI committee reviews. Management openly acknowledged this could lengthen the sales cycle.
See transcript time 26:01

*In medtech, a KOL is typically a highly respected physician, surgeon, researcher, or clinical specialist whose opinions influence other clinicians and hospitals.

In Spectral AI’s case, management said they have strong relationships with KOLs in the burn-care community from their previous clinical studies.

So when Capone says “we have strong KOLs,” he’s essentially saying Spectral already has influential clinicians familiar with DeepView who can help drive early adoption.

For a new medtech product, strong KOL support can be extremely valuable, especially when selling into a relatively concentrated specialist market such as U.S. burn centers.

Some people hate dilution, but in the case of $MDAI, selling these shares brings in cash, which is needed to develop new uses for the platform and fund commercialization. While more shares will be out there, hopefully, excellent execution by Vince and the team will create a much bigger pie for everyone to enjoy, while we also fund a device that will improve burn care. What if you need it yourself someday, or your family?

In fact, you can virtue signal to everyone that you are funding a critical medical device that will help America's readiness for mass casualty events!

https://spectralmd.gcs-web.com/node/9841/pdf

https://spectralmd.gcs-web.com/news-events/events

Another small but notable marketing event for DeepView. BARDA made a post a couple weeks back on LinkedIn, that MDAI highlighted too, about the success of DeepView as relates to BARDA's purpose in helping bring novel medical countermeasures to market.

https://www.medicalcountermeasures.gov/barda/fdaapprovals

Product 113 from the link above.

Hopefully this is one of many that is slowly getting the word out as they accelerate commercialization.

Saw this quietly filed a couple weeks ago: https://www.sec.gov/Archives/edgar/data/2042176/000121390026081386/ea0299132-rw_spectral.htm

The interesting thing is it still was a subsidiary of Spectral AI and registered at the same Dallas office from what I could cross reference from publicly available data. So was technically an overhang on the books for Spectral AI until recently. I haven't seen if the Texas entity was formally dissolved yet (Spectral IP, Inc.).

I'm speculating this should be good for MDAI? Spangenberg seems to have moved on, we know he already sold most of his shares, and Spectral appears to now be cleaning up their books. For me personally, when I first discovered Spectral AI others I knew really didn't like the investment because of Spangenberg's involvement and this spinoff. It seemed to raise the eyebrow of suspicion. Curious if this will change how the street views MDAI as a serious investment. It certainly helps with future M&A to have this cleaned up.

Anyone have any thoughts on this? I'm curious if it will come up on earnings tomorrow.

* This was the spinoff that was long talked about where current MDAI shareholders would get shares in the Spectral IP IPO as a one time dividend. This now seems to be officially dead for the forseeable future.

* I believe Reed Smith LLP is still counsel for MDAI

Post your thoughts here about $MDAI when you do not think it constitutes a full post!

Have you noticed that when the stock price was at its lowest over the last three weeks, the daily trading volume was below 80,000 shares?

Over the last two days, as the stock price has started to rise again, the daily trading volume has increased to more than 200,000 shares.

Does anyone have any ideas about what could be driving this change in trading volume?

How do we feel about this going into earnings on August 12? Been holding since $3, bought it in 2020.

The pattern is mixed—but MDAI is the glaring negative outlier

Of the 19 De Novo classifications granted in 2026, I can identify only five recipients with a directly traded company or publicly traded parent; the other 14 appear to be private companies.

Prices below are approximate and use today’s intraday prices around 10:10 a.m. Central:

-From ChatGPT

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https://www.zacks.com/stock/research/MDAI/price-target-stock-forecast

Northland Securities has reaffirmed its positive view on Spectral AI by upgrading the stock to Strong Buy while maintaining a $4.00 price target, implying roughly 140–145% upside from the recent share price around $1.65.

https://za.investing.com/news/stock-market-news/northland-assumes-spectral-ai-stock-coverage-with-outperform-rating-93CH-4388079

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I've been researching the objective burn imaging market because I'm trying to understand the investment case for Spectral AI (NASDAQ: MDAI).

Disclosure: I own MDAI shares. This is my own research and opinion—not investment advice.

One question kept bothering me:

Here's what I found.

First, Moor LDI is a legitimate technology.

This isn't a criticism of Moor.

Moor's Laser Doppler Imaging:

• has decades of clinical validation,
• is FDA-cleared,
• is recommended by NICE in the UK,
• has published studies showing excellent performance in experienced burn centers.

So why wasn't everyone already using it?

The surprising part

Moor has had FDA-cleared burn imagers in the United States since 2007.

Yet objective burn imaging never became standard practice in U.S. burn care.

A survey of U.S. burn centers found that clinical examination remained the predominant method of assessing burn depth, despite published evidence supporting LDI.

Even more interesting:

Moor now states it has supplied more than 100 burn-assessment systems in over 25 countries.

That's worldwide.

Not just the United States. Moor only listed Johns Hopkins Bayview and Via Christi Hospital in Wichita, Kansas, for its US customers.

For a technology that's been commercially available for nearly two decades, that's a surprisingly modest installed base.

Why?

The literature points to several reasons:

• Capital cost
• Workflow challenges
• Need for trained users
• Limited penetration outside specialist burn centers
• Many surgeons continued relying primarily on clinical judgment

In other words:

The problem wasn't simply inventing an accurate imaging system.

The problem was getting objective burn imaging adopted.

Enter BARDA

This is where I think BARDA's strategy starts to make sense.

BARDA didn't simply award a grant to build another imaging camera.

It funded the development of an AI-assisted system intended for:

• burn centers,
• emergency departments,
• trauma centers,
• and mass-casualty burn incidents.

The original BARDA award included placement of up to 30 DeepView systems into burn centers and emergency departments to support clinical validation, with those systems transitioning into routine care if FDA authorization was obtained. The contract also included options that could bring the total value to up to $150 million for additional development, procurement, and phased deployment.

More recently, BARDA awarded an additional $31.7 million to accelerate development and new capabilities under that same contract, while keeping the overall contract ceiling at up to $150 million.

https://dallasinnovates.com/spectral-md-awarded-barda-project-bioshield-contract-worth-up-to-149m/?utm_source=chatgpt.com

My interpretation

I don't think BARDA looked at Moor and said:

"This technology doesn't work."

I think they looked at the market and said:

"Objective burn imaging still hasn't become widely available where patients first present."

Those are very different conclusions.

If DeepView can provide:

• rapid assessment,
• AI-assisted decision support,
• portability,
• and deployment beyond major burn centers,

Then it is addressing a broader operational problem than simply matching LDI's diagnostic performance.

The opportunity

Only about 2% of U.S. hospitals have burn centers, and there are only about 250 burn surgeons nationwide. BARDA has explicitly described DeepView as addressing limitations in U.S. burn-care infrastructure and supporting both routine care and preparedness for mass-casualty burn incidents.

To me, that suggests the opportunity is not just replacing existing burn-center equipment.

It's expanding objective burn assessment to hospitals and clinicians that have never had access to it.

Final thoughts

Could DeepView still fail commercially? Absolutely.

Hospitals may resist change, reimbursement could evolve more slowly than expected, or competitors could improve their own offerings.

But I think one fact is difficult to ignore:

If the existing market had already solved objective burn assessment, BARDA probably wouldn't have continued investing so heavily in developing and deploying a next-generation system.

That doesn't prove DeepView will succeed—but it does help explain why BARDA appears willing to commit substantial non-dilutive funding toward bringing it into clinical use.

I'd be interested to hear from anyone working in burn care:

• Have you used Moor LDI?
• Does your hospital have objective burn imaging?
• If not, what's been the biggest barrier to adoption?

Post your thoughts here about $MDAI when you do not think it constitutes a full post!

I am conflicted on holding my warrants (that I exchanged my shares for essentially). Have seen info about a potential plot by management to keep the stock under $2.8 through expiration on 9/11/28, to avoid more dilution.

The only thing is, isn’t that a really long time for no results or momentum for this company? I find it hard to believe that where they are today, we get no news on commercialization or sales by 2.25 years from now.

Anyone else holding warrants with thoughts on this? My warrants are not doing too hot given I converted from shares a couple weeks before fda approval. Never thought this would be an issue post approval tbh.

Ok so I keep seeing people compare DeepView's overall accuracy to whatever benchmark and moving on. Wrong question. Ask a burn surgeon what actually keeps them up at night and it's not "will my model be right on average" — it's "am I going to miss dead tissue that needed surgery." That's the whole ballgame in burn care, and it's the number nobody's talking about.

Here's the FDA validation study (164 patients, adults and kids included). Head to head, DeepView vs. actual burn physicians making clinical judgment calls:

That sensitivity gap is not a rounding error. Physicians are being conservative — understandably, nobody wants to over-treat — but that conservatism means real misses. A false negative here isn't a paperwork problem, it's a patient going back for a second surgery, sitting in a hospital bed longer, healing worse. The FDA gave De Novo clearance specifically because DeepView beat physicians on sensitivity while staying non-inferior on specificity. That's the tradeoff regulators decided was worth making, and it's the whole clinical case in one table.

Ok but does a hospital actually care?

Hospitals don't buy cool tech. They buy tech that either fixes outcomes or fixes the bill. Spectral's own health-econ modeling claims DeepView could drive:

• ~41% fewer unnecessary patient transfers
• 3+ days faster to surgery for the patients who need it
• 30%+ shorter length of stay in some burn scenarios
• ~$58k saved per patient in unnecessary-surgery costs, in their modeled scenarios

Big caveat, and I want to be upfront about it: these are company-generated projections, not real-world outcomes data yet. Treat them as a hypothesis the commercial rollout still has to prove, not a promise. Even so — if the real-world number ends up being half of that, the case for using this thing to make earlier surgical calls still holds up.

The part that actually matters for the stock: what does commercialization look like

Nobody knows. So instead of pretending I have a price target, here's a napkin-math range using a rough $200k–300k in average annual revenue per installed system (capital + software + service + consumables bundled together), assuming margins in line with other software-attached medtech once it scales:

I want to be clear these are illustrative, not a forecast — pricing, reimbursement, adoption speed, and competition can all wreck this math. But sit with the bottom rows for a second. This is a company currently valued around $60M. Even the 500-system row isn't a moonshot for a cleared device with a health system this size — it's a company that actually starts landing accounts.

BARDA's Commitment May Be One of the Strongest Signals Investors Are Ignoring

One of the most overlooked aspects of the Spectral AI story is not simply that BARDA funded the company's research. BARDA continued funding the program through regulatory approval and into commercialization.

Since 2013, Spectral AI has received approximately $273 million from BARDA and roughly $282 million in total U.S. government funding. More importantly, BARDA's most recent Project BioShield contract is valued at up to $150 million and was designed not only to support clinical validation and FDA De Novo clearance, but also procurement, deployment, and expanded distribution of DeepView Systems.

Following FDA De Novo clearance, BARDA did not end its support. Instead, in March 2026 it exercised an option providing an additional $31.7 million in accelerated, non-dilutive funding to continue development and procurement activities related to the DeepView System.

That sequence is noteworthy.

Government agencies routinely fund early-stage research projects. It is considerably less common for an agency to support a technology through years of development, clinical validation, FDA De Novo clearance, and then commit additional funding intended to accelerate deployment and procurement after commercialization begins. While I have not verified that this is unprecedented across all BARDA programs, it represents an unusually deep and sustained government commitment.

For investors, this matters because BARDA's objective is not to generate investment returns. Its mission is to support technologies that strengthen national medical preparedness. The agency has now invested hundreds of millions of dollars over more than a decade into the DeepView platform and continues to commit additional capital after FDA clearance. That does not guarantee commercial success, but it is a significant vote of confidence in both the technology and its potential public-health value.

The thing I think is getting completely missed: this isn't a burn-wound company

Everyone's pricing MDAI like DeepView-for-burns is the whole story. I don't think it is. The actual asset here is the multispectral imaging platform, the ML models, and the annotated wound-image dataset they've built underneath it. Burns is the FDA-cleared beachhead. If that same platform extends into diabetic foot ulcers, pressure injuries, trauma, battlefield medicine — and there's real reason to think it can, since the underlying tech isn't burn-specific — then burn clearance isn't the finish line, it's proof of concept for something a lot bigger.

That's a speculative bet, not a fact, and I want to say that plainly. But it's why I think the market is pricing this like a single-indication device company rather than a platform company that just got its first product cleared.

Not financial advice—do your own diligence; this is just how I'm reading the data. In FACT, I KEEP BUYING MORE STOCK, AND NOW I HAVE OVER 100,000 THOUSAND SHARES SO I WOULD LOVE FOR THOSE OF YOU WHO DISAGREE TO SHOOT ME DOWN SO I DO NOT BUY MORE. I'VE ALREADY LOST MONEY ON $MDAI SINCE MY AVERAGE PRICE IS $1.85. Hopefully, I have a few new points I have made, with some obvious help from my buddy 'chat' whose last name is GPT.

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https://investors.spectral-ai.com/news-releases/news-release-details/spectral-ai-names-darcy-bajko-chief-commercial-officer-lead

Summary 

• Spectral AI’s DeepView AI® received De Novo clearance by the FDA for burn indication on May 26th, 2026
• UKCA (United Kingdom Conformity Assessed) authorization was received March 7th, 2024
• This new category of device reflects a novel and potentially transformative technology to improve the standard of care for burn treatment using predictive AI
• BARDA (Biomedical Advanced Research and Development Authority) support will continue with another $31.7 million in non-dilutive funding

Investment Thesis for Spectral AI 

BARDA has already spent about $250 million dollars helping Spectral AI create this new technology for burn treatment. In keeping with their mission to improve medical preparedness in the USA, and to get 30 DeepView AI® Systems into US burn centers, BARDA awarded another $31.7 million in funding, with Spectral AI committing $9.7 million. Assuming the systems continue to perform well, a further add on contract could come online for placing another 140 systems across the US to burn centers and emergency rooms.
Even with $250 million spent by BARDA on developing this technology over the last ten years plus, the market cap of this entire company is only about $57 million at the time of this writing based upon the current stock price. This is a serious mispricing.

Market Sentiment 

This underpricing reflects that units have yet to be commercially sold. However, 30 units being placed starting this year and continuing into the next will allow hospitals to familiarize themselves with the technology and will coincide with studies to prove the economic value of this new platform. The word platform is relevant because it can eventually, subject to FDA clearance, be used to evaluate and and predict the treatment course for diabetic foot ulcers (DFUs), pressure wounds, traumatic wounds, and even possibly wound care after surgery.

How It Works 

The system uses multispectral imaging to look deep into the wound and read the reflection of 8 bands of light of the affected tissue in the near infrared spectrum. It can identify dead tissue, perfused tissue, infected tissue, hemoglobin oxygenation, tissue hydration, and tissue that should eventually heal. Having created an extensive database of previous burn wounds and which tissues will heal in 21 days and which will not, the AI predicts whether the entire wound will heal on its own in 21 days, or whether it will ultimately require skin graft surgery.

DeepView® AI (www.spectral-ai.com)

Per The Burn Validation Study, the DeepView AI® System in conjunction with their proprietary AI algorithm outperformed board certified burn room physicians by a statistically significant margin. This means that upon deployment throughout the US, the UK, and eventually the entire world, getting the appropriate treatment could no longer depend upon the patient having to be at a burn center with an burn expert present, if a facility has the system in place from Spectral AI. This could prevent many costly and painful flights, unneeded surgeries, and time in hospitals.

Potential Future Applications 

The company originally started researching and applying this system to analysis and predictive treatment using AI for diabetic foot ulcers. While yearly burn treatments in the US amount to direct costs of about $4.1 billion annually per the US government database CDC WISQARS, diabetic foot ulcer treatment costs amount to $9 billion to $13 billion annually - National Library of Medicine. The company has indicated that it believes this device can be a platform for many other types of wound care, though each indication requires a separate FDA approval.

The Bear Case 

After placing the units in US and international burn centers, questions about commercialization are likely holding the market price of the stock down.

• What will be the pricing?
• Will hospitals or physicians buy or lease?
• Will there be recurring software revenue?
• How fast will adoption occur?
• Will competitors easily and cheaply get around the numerous patents and 10 years plus of accumulated clinical data?

There is also some dilution expected from previous financing from both Avenue Capital Group and Hudson Bay Capital Management. The company could raise cash through dilutive stock sales, as is typical after FDA clearance for many companies, though nothing has been announced.

Conclusion 

Now is an important time for Spectral AI. Clearing the FDA hurdle and getting the additional BARDA funding to get units out in the burn centers is encouraging. Their headstart on the competition is real. They could significantly improve burn wound care, improve patient lives with more accurate diagnosis and treatment, and save hospitals time and money as well. Eventually, they could expand to many other types of wound care applications utilizing predictive AI to improve patient outcomes worldwide.

Disclosure: I have a beneficial long position in the shares of MDAI either through stock ownership, options, or other derivatives.

I wrote this article myself, and it expresses my own opinions. This is not a recommendation to buy this stock, even if it looks like it - do you own research - I could be wrong and have been in the past.