Adam Flanders, MD

Neuroradiologist Thomas Jefferson University Hospital

[Adam Flanders, MD @BFlanksteak]

New paper out in npj Health Systems! An ensemble of local, open-source LLMs can automatically monitor clinical AI performance in real time — no radiologist review needed. The foundation of our RADAR system. 🧵
https://t.co/bZ1TIo5MRw
#RadiologyAI #LLM #HealthInformatics

[Adam Flanders, MD @BFlanksteak]

https://t.co/uVOaypEN0r

[Adam Flanders, MD @BFlanksteak]

“Why Do Most AI Startups Keep Failing in 2025?” by Sahin Ahmed, Data Scientist https://t.co/Aq90JVxvaP

[Adam Flanders, MD @BFlanksteak]

The Evolution of Radiology Image Annotation in the Era of Large Language Models | Radiology: Artificial Intelligence https://t.co/yXPybjsVI7

[Charles Kahn, MD @cekahn]

Excellent article on #AI in #radiology by @SteveLohr in today's @nytimes:

Your A.I. Radiologist Will Not Be With You Soon https://t.co/hovX0GEt8J

@Radiology_AI @PennMDForum @PennRadiology

[The Medical Imaging and Data Resource Center @MIDRC_]

Join us April 15 (2–2:45pm CT) for MIDRC’s free virtual seminar!

Topic: ChatGPT – DICOM De-Identification

Register here: https://t.co/Ecgyuii3Am

#MIDRC #ChatGPT #DICOM #AIinHealthcare

[University of Michigan @UMich]

Big Ten Champs! Congrats, @UMichBBall!
#GoBlue 💛💙

[Yoshimi Anzai @yoshimianzai]

Love to see you all in Philadelphia! @rhwiggins @amyfjuliano @tabby_kennedy @EMiddlebrooksMD @suzie_bash @ENThawk

[Adam Flanders, MD @BFlanksteak]

Frequent AI use may increase radiologists’ risk of burnout https://t.co/7khzznmfZP

[Vishnu Vettrivel @vishfulthinkr]

⚠️ AI Hallucinations: What Every Developer Needs to Know 💡

AI hallucinations aren't just glitches—they can lead to significant risks, from downtime costs to legal issues. For #AI developers working with #LLMs, it's essential to understand how to detect and prevent these errors to build trustworthy models. Here’s what you need to know. 🧵 [1/3]

[Radiology: Artificial Intelligence @Radiology_AI]

#RATIC is the largest & most geographically diverse, publicly available expert-annotated dataset of abdominal trauma CTs https://t.co/O94lO0Vngh @RSNA @KMagudia  @UHradiology #trauma #injury #MachineLearning

[Radiology: Artificial Intelligence @Radiology_AI]

RSNA Abdominal Traumatic Injury CT (RATIC) dataset contains 4274 abdominal CTs with annotations related to traumatic injuries https://t.co/O94lO0Vngh @MonganMD @lmprevedello @BFlanksteak #trauma #injury #ML

[Radiology: Artificial Intelligence @Radiology_AI]

Radiologists and #AI scientists working together -- and the challenges ahead for AI https://t.co/GtiuTtntOq #AIME24 #AIME2024 #AI

[Charles Kahn, MD @cekahn]

Read the perspectives of experts from @MICCAI_Society and @RSNA on the clinical, cultural, computational, and regulatory considerations to adopt #AI technology successfully in radiology https://t.co/CsPEVa2O1R #AIME2024

[SIIM @SIIM_Tweets]

Coming soon: #SIIM chair @asset25 will share an exclusive, behind-the-scenes look at SIIM's priorities at the #SIIM24 Membership Meeting! Join us to celebrate SIIM Awardees & meet SIIM Leadership!

Jun 28 | National Harbor, MD
https://t.co/eBDetJU2ku

[Curt Langlotz @curtlanglotz]

All the CheXpert Plus links in one place:
--Dataset: https://t.co/9ZkvmBTmbg
--Arxiv paper: https://t.co/ggwx6QOS74
--De-ID algorithm paper: https://t.co/DeQvoo9tsw
--Hugging Face De-ID algorithm: https://t.co/28n6hq2X6s

@StanfordAIMI

[Curt Langlotz @curtlanglotz]

Contrastive learning and the study of algorithmic fairness require more and different CheXpert data. To meet this need, we are releasing CheXpert Plus, including radiology reports, demographic data, DICOM images, pathology labels, & RadGraph extractions. https://t.co/qtRn3iZB0a

[Curt Langlotz @curtlanglotz]

Five years ago, thanks to the leadership of @mattlungrenMD, @stanfordAIMI released the CheXpert images: 223K JPG CXRs with labels for 14 conditions. CheXpert has been cited >6000 times, mostly related to development of supervised learning methods. Much has changed since then.🧵

[The Medical Imaging and Data Resource Center @MIDRC_]

Join us today!

Our May seminar is happening today at 2pm CT and featuring research on "The MIDRC Diversity Calculator: A Dynamic Tool for Measuring and Monitoring the Representativeness of Biomedical Datasets."

Registration here: https://t.co/Ecgyuii3Am

[Woojin Kim @woojinrad]

Many-Shot In-Context Learning in Multimodal Foundation Models

🤔 They benchmarked GPT-4o and Gemini 1.5 Pro using 10 datasets and found that many-shot ICL results in significant improvements compared to few-shot ICL across all datasets.

https://t.co/ERSX75DNUi