🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

Elisabeth Bik, expert in scientific integrity: ‘We need to slow down scientific publishing’ | Science | EL PAÍS English english.elpais.com/science-tech/2…

#AI competitions have engaged a global community to effectively address real-world medical problems doi.org/10.1148/ryai.2… Felipe Kitamura @slowvak Matthew Lungren MD MPH #DeepLearning #MachineLearning #competition

The latest Radiology AI competition -- lumbar spine degenerative disease -- just went live on Kaggle ! Great opportunities for both radiologists and data scientists; come join the fun! kaggle.com/competitions/r…

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. buff.ly/44LGYn8

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: us06web.zoom.us/webinar/regist…

Five years ago, thanks to the leadership of Matthew Lungren MD MPH, @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.🧵

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. arxiv.org/abs/2405.19538

All the CheXpert Plus links in one place: --Dataset: aimi.stanford.edu/shared-datasets --Arxiv paper: arxiv.org/abs/2405.19538 --De-ID algorithm paper: academic.oup.com/jamia/article-… --Hugging Face De-ID algorithm: huggingface.co/StanfordAIMI/s… Stanford AIMI

Coming soon: #SIIM chair Tessa S. Cook MD PhD CIIP FSIIM FCPP FAAR 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 ecs.page.link/rZwqZ

Read the perspectives of experts from MICCAI and RSNA on the clinical, cultural, computational, and regulatory considerations to adopt #AI technology successfully in radiology doi.org/10.1148/ryai.2… #AIME2024

Radiologists and #AI scientists working together -- and the challenges ahead for AI doi.org/10.1148/ryai.2… #AIME24 #AIME2024 #AI

RSNA Abdominal Traumatic Injury CT (RATIC) dataset contains 4274 abdominal CTs with annotations related to traumatic injuries doi.org/10.1148/ryai.2… John Mongan Luciano M Prevedello MD MPH Adam Flanders, MD #trauma #injury #ML

#RATIC is the largest & most geographically diverse, publicly available expert-annotated dataset of abdominal trauma CTs doi.org/10.1148/ryai.2… RSNA Kirti Magudia, MD PhD  @UHradiology #trauma #injury #MachineLearning

⚠️ 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

Frequent AI use may increase radiologists’ risk of burnout radiologybusiness.com/topics/artific…

Love to see you all in Philadelphia! Richard Wiggins Amy Juliano Tabby A. Kennedy, MD Erik Middlebrooks, MD Suzie Bash Ashley Aiken

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

Join us April 15 (2–2:45pm CT) for MIDRC’s free virtual seminar! Topic: ChatGPT – DICOM De-Identification Register here: us06web.zoom.us/webinar/regist… #MIDRC #ChatGPT #DICOM #AIinHealthcare

Excellent article on #AI in #radiology by Steve Lohr in today's The New York Times: Your A.I. Radiologist Will Not Be With You Soon nytimes.com/2025/05/14/tec… Radiology: Artificial Intelligence Penn Medicine MD Penn Radiology

The Evolution of Radiology Image Annotation in the Era of Large Language Models | Radiology: Artificial Intelligence pubs.rsna.org/doi/10.1148/ry…