Tinglong Dai
@tinglongdai.com
52 followers 110 following 31 posts
Ferrari Professor of Business, JohnsHopkins; VP INFORMS ✍🏻 AI, Supply Chains, & Healthcare
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Reposted by Tinglong Dai
jamahealthforum.com
FDA-cleared #AI medical devices often experience recalls shortly after clearance, particularly those without clinical validation and produced by publicly traded companies. ja.ma/3UFrZqI
tinglongdai.com
Medical AI is as much about forgetting as it is about learning.

Even if data are deleted, models can still remember what they learned. That’s why “machine unlearning” is emerging as a crucial frontier for privacy, regulation, and trust.

New in Health Affairs: www.healthaffairs.org/content/fore...
Unlearning In Medical AI: A New Frontier For Privacy, Regulation, And Trust | Health Affairs Forefront
Even if data are removed from a system, it’s possible that an AI model may still be retaining the ‘lessons’ it learned from training on that data in the past.
www.healthaffairs.org
Reposted by Tinglong Dai
jamahealthforum.com
FDA-cleared #AI medical devices often experience recalls shortly after clearance, particularly those without clinical validation and produced by publicly traded companies. ja.ma/4lFOjeA
Figure 2.  Recall Counts, Cause, and Affected Units by Commercialization Model
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Thank you for spotlighting our study!
Reposted by Tinglong Dai
smcgrath.phd
A study finds clinicians rate peers who use generative AI for primary decision-making lower in skill and competence. Framing AI as a verification tool partially mitigates this negative perception but does not eliminate it.
#MedSky #MLSky #MedAI
Peer perceptions of clinicians using generative AI in medical decision-making - npj Digital Medicine
npj Digital Medicine - Peer perceptions of clinicians using generative AI in medical decision-making
www.nature.com
tinglongdai.com
Grateful to work with a dream team:

Drs. Haiyang Yang, Risa Wolf, Nestoras Mathioudakis, & Amy Knight @jhu.edu @hopkinsmedicine.bsky.social
plus Dr. Yuna Nakayasu, my former MBA/MPH student @johnshopkinssph.bsky.social @jhu.edu, now of McKinsey
tinglongdai.com
Yet, clinicians also saw promise:

Belief that GenAI improves accuracy: 4.30

Institution-customized GenAI viewed even more favorably: 4.96

(7-point scale)
tinglongdai.com
Ratings of the care experience also dropped — from 4.48 ⭐️ to 3.08 ⭐️ (5-star scale).

Framing GenAI as a verification tool helped (clinical skill 4.99, competence 4.94), but the gap remained.
tinglongdai.com
The numbers are striking.

In our randomized experiment of 276 clinicians, a physician who used GenAI as a decision aid tool was rated far lower:

Clinical skill: 3.79 vs 5.93

Overall competence: 3.71 vs 5.99

(7-point scale)
tinglongdai.com
Would you trust a doctor who uses ChatGPT during your visit?

Today, we published a study in @natureportfolio.nature.com Digital Medicine — the first survey of practicing clinicians on how they view peers who use generative AI in medical decision-making.
🔗 nature.com/articles/s41...
Peer perceptions of clinicians using generative AI in medical decision-making - npj Digital Medicine
npj Digital Medicine - Peer perceptions of clinicians using generative AI in medical decision-making
nature.com
tinglongdai.com
Grateful to Branden Lee, Shivam Patel, CrystalFavorito, Sara Sandri, and Maria Rain Jennings, first- and second-year @jhu.edu medical students already shaping medical AI.

Thanks also to Drs Charlotte Haug and Isaac Kohane of @ai.nejm.org for thoughtful guidance.

(6/7)
tinglongdai.com
Safety gap

@fda.gov-cleared AI devices from publicly traded firms are recalled far more often: up to 30 × compared with those from private firms (14.4% vs 1.3% of cleared devices)

Development and commercialization models corrects with patient risk and should guide oversight.

(5/7)
tinglongdai.com
Tech under the hood

Deep learning now powers half of new @fda.gov-cleared devices.

Transparency is improving, yet 62% of all devices still give little or no detail about how their AI works.

(4/7)
tinglongdai.com
AI Clearance curve

Average @fda.gov clearances jumped from 1.4 devices per year in 1995-2014 to 146 per year in 2020-24—a 100-fold surge.

Total count went from 27 in the first 20 years to 729 in the last five.

In-house development drives nearly all growth.

(3/7)
tinglongdai.com
Who is building what?

69% of @fda.gov-cleared AI device manufacturers are private, but public firms make more devices per company.

General Radiology leads with 32%, followed by cardiovascular (18%) and neuropsychiatry (15%).

A booming yet scattered market.

(2/7)
tinglongdai.com
Honored to lead an incredible team of @jhu.edu medical students on the first full look at how @fda.gov-cleared medical AI devices are developed and commercialized, now in @ai.nejm.org.

We tracked 950 AI medical devices. The results may surprise you: bit.ly/fdaai25

(1/7)
Reposted by Tinglong Dai
tinglongdai.com
5/5 As a top exporter leading in diagnostic and lab reagents, a prolonged trade war could render the global scientific supply chain more fragile, costly, and unreliable.​

We may be at the onset of a tariff-induced chaos period.​
tinglongdai.com
4/5 The U.S. imports billions in lab equipment and reagents annually; many now face 10–54% tariffs.​

Even U.S.-built DNA sequencers may rely on German optics or Chinese semiconductors.​

High-end tools like precision microscopes aren't produced domestically.​
tinglongdai.com
As I told @celestebiever.bsky.social of @nature.com, “These aren’t luxury items. They’re the core infrastructure of modern science.”
tinglongdai.com
2/5 These tariffs hit essentials—from basic labware to advanced instruments—just as research institutions face severe financial strain. NIH funding is down 60% in Q1, and indirect cost recovery is under fire.

This isn’t belt-tightening; it could be a breaking point.