@DavidToroT

Endocrinologist and Assistant Professor @MayoClinic, Internist @gtown_medres, MD @UniversidadCES. Views are my own.

 Minnesota, USA
Joined May 2018
  • Tweets256
  • Following357
  • Followers737
31Media
David Toro Tobon retweeted
Spyridoula Maraka@endofellowSep 16
Our team has received a $3.6M @NIHAging R01! 🎉 We’ll study whether #LT4 can be safely discontinued in older adults with subclinical #hypothyroidism. Grateful to our patients, collaborators & research teams who made this possible! @DeptVetAffairs @MayoClinicEndo @UFHealth
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The latest in how #ArtificialIntelligence is changing the game for #thyroidnodule evaluation. @DavidToroT discusses the data in #ClinicalThyroiology. ow.ly/x0Rq50ZwBtb #endotwitter #medtwitter #thyroid @Sage_Publishing
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Thyroid overdiagnosis costs $25B annually. In @clinicalthyroid , I review how an AI adapter refines ultrasound risk via pixel-level analysis, matching experts (AUC 0.794) and preventing 55.7% of unneeded biopsies to cut costs @mayoclinicendo l1nq.com/p6p9pkl
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How to read an AI study like a peer reviewer. A practical eight-question framework helps clinicians identify trustworthy #AI studies. #MedTwitter #EndoTwitter aaceendocrine.ai/quark-uploa… @TheAACE #EndocrineAI

How to read an AI study like a peer reviewer

aaceendocrine.ai
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Just like a resident memorizing practice exams, an AI that memorizes training data will fail in the real world. In my latest for @TheAACE Endocrine AI, I explore overfitting, data leakage, and the critical skepticism clinicians need tinyurl.com/2s3z67vb @MayoClinicEndo

How AI models learn (and overlearn): AI Tutorial Series

aaceendocrine.ai
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Time to challenge the "lifelong" levothyroxine dogma? In Clinical Thyroidology, I review new data: 64% of older adults on ≤50 µg/day successfully stopped at 1 yr. But relaxed TSH targets & long-term unknowns require a careful approach tinyurl.com/3tk6nhsx @MayoClinicEndo
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Our latest @MayoClinicEndo study uses AI to expose a major driver of thyroid cancer overdiagnosis: incidental findings on routine CT/MRI scans. We built an NLP pipeline to analyze 115,683 patients over 6 years. The data: 🧵 doi.org/10.1210/clinem/dgag1… @doctorjuanpa

Artificial intelligence-enabled analysis of radiology reports: epidemiology and outcomes of...

AbstractContext. Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features,

academic.oup.com
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• The diagnostic cascade is massive: an incidental finding led to 46.8x higher odds of biopsy, 55.8x higher odds of total thyroidectomy, and 61.7x higher odds of a cancer diagnosis. • 88.1% of these detected cancers were small, low-risk papillary carcinomas. 🧵
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Current management shifts patients toward invasive procedures for subclinical disease unlikely to cause harm. We need standardized cross-sectional imaging reporting & far more selective follow-up protocols.
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Our recent commentary examines AI-enhanced molecular diagnostics for thyroid nodules. While combining AI & genetics could improve precision, small cohorts and NIFTP classification remain hurdles to clear before clinical reality @MayoClinicEndo @TheAACE doi.org/10.1016/j.eprac.2026…
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The "clinician in the loop" model is a flawed solution for AI oversight. It shifts accountability from developers to doctors, making clinicians the "moral crumple zone" for system failures. Our new BMJ analysis: 🧵 doi.org/10.1136/bmj-2025-089… @MayoClinicEndo @doctorjuanpa
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We propose an alternative: "AI as adviser". AI should operate in the background to support the therapeutic alliance, rather than mediating it.
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Safe AI requires shifting from bedside vigilance to system-level safeguards. This relies on three pillars: - ​Enterprise accountability and shared risk - ​Institutionalized stakeholder governance - ​Continuous automated monitoring. ​Responsibility belongs upstream
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David Toro Tobon retweeted
The BMJ
@bmj_latestMay 5
Regulators and health systems increasingly rely on human oversight at the point of use as a primary safeguard for AI. “Clinician in the loop” oversight shifts responsibility for AI safety from developers to doctors bmj.com/content/393/bmj-2025…

Clinician in the loop: a flawed solution for AI oversight

David Toro-Tobon and colleagues argue that “clinician in the loop” is shifting responsibility for AI safety from developers to doctors and cannot be relied on as a failsafe for patients Consider a...

bmj.com
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Build practical diabetes management skills with the Essential Diabetes Care online course—recorded lectures and case studies in a self‑paced 9+ hour online format for providers. Learn more: tinyurl.com/r29x45na #CME #Diabetes
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At @MayoClinicEndo, we are evaluating next-gen therapies targeting the root causes of thyroid autoimmunity. Explore our active clinical trials for Graves' disease and TED here: tinyurl.com/4s9bbykh #Endocrinology #ClinicalTrials
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David Toro Tobon retweeted
Jairo Noreña MD.
@DrJairoNorenaApr 24
Colombias in Endocrinology at @TheAACE! Un gusto toparme con @DavidToroT! #AACE2026
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Practical tips for using AI in clinical practice. Great session by @DavidToroT at #AACE2026
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