Welcome to Deep Learning Labs of RSNA or Radiologic Society of North America 2025 Annual Meetings. Here you will find the materials and coding notebooks of different workshops within their subsequent folders. The schedule for the workshops is as follows—feel free to visit each session’s folder for hands-on resources and instructions.
Note: The dates and times below may be subject to change. For the most up-to-date schedule of the event, please visit the RSNA 2025 Annual Meeting Schedule.
| Date | Time | Session | Moderator | Speakers |
|---|---|---|---|---|
| Nov 30, 2025 | 10:30 AM | Basics of Natural Language Processing in Radiology | Jae Ho Sohn MD MS | Timothy Chen MD; Gunvant Chaudhari MD; Cody Savage MD |
| Nov 30, 2025 | 2:30 PM | ChatGPT – DICOM De‑Identification Using ChatGPT | George Lee Shih MD MS | Adam Eugene Flanders MD; Errol Colak MD; Lisa Adams |
| Dec 1, 2025 | 8:00 AM | Quantifying Uncertainty in Deep Learning | Bradley Erickson MD PhD | Shahriar Faghani MD; Mana Moassefi MD |
| Dec 1, 2025 | 9:30 AM | Data Extraction from Radiology Reports with LLMs | Walter Wiggins MD PhD | Mindy Yang MD |
| Dec 2, 2025 | 1:30 PM | Leveraging Pre‑Trained Embeddings Models for Your Use Cases and Your Data | Rory Pilgrim Beng | Daniel Golden PhD; Jason Klotzer |
| Dec 2, 2025 | 4:30 PM | Patient‑Centered Representations with Multi‑Modal Graphs | Dimitri Falco PhD | Deborah Langman |
| Dec 3, 2025 | 8:00 AM | An Introduction to Multi‑agent Artificial Intelligence Systems in Radiology | Pouria Rouzrokh MD MPH MHPE | Moein Shariatnia MD; Melina Hosseiny MD |
| Dec 3, 2025 | 9:30 AM | Transforming Radiology with LLMs: Fine‑Tuning and Explainable AI for Next‑Gen Clinical Solutions | Paul Yi MD | Briana Malik BS; Dharmam Savani MS |
Please visit each of the following deep learning folders to see the educational materials for each deep learning lab.
- DL Lab: Basics of Natural Language Processing in Radiology
- DL Lab: ChatCTP - DICOM de-identification using ChatGPT
- DL Lab: Data Extraction from Radiology Reports with LLMs
- DL Lab: Quantifying Uncertainty in Deep Learning
- DL Lab: Leveraging pre-trained embeddings models for your use cases and your data
- DL Lab: Patient-Centered Representations with Multi-Modal Graphs
- DL Lab: An Introduction to Multi-agent Artificial Intelligence Systems in Radiology
- DL Lab: Transforming Radiology with LLMs - Fine-Tuning and Explainable AI for Next-Gen Clinical Solutions