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 Exploring Foundation Models in Digital Pathology: Insights and Tools

In today's DigiPath Digest we talk about the foundation models in pathology.
reviewing abstracts from two notable papers in Nature.

We discuss the high-level overview of these models, including Hamid Tizhoosh's insights on the vast data requirements for developing effective foundational models.

We also explore tools for literature research, comparing PubMed and Undermind.ai, and examine a useful children's book on artificial intelligence :)

The episode features audience interaction and offers updates on digital pathology trends, along with a personal anecdote on the nature of comparison based on a yoga class experience.

00:00 Introduction and Overview
00:16 Foundation Models in Pathology
00:33 Comparing Research Tools
01:03 Live Stream Interaction
01:12 Starting the Podcast
04:51 Foundation Models Explained
05:11 Research and Findings
06:34 Children's Book on AI
08:00 Deep Dive into Foundation Models
14:28 Case Studies and Examples
18:18 Discussion on Data and Models
21:00 Final Thoughts and Questions
26:24 Exploring ToxPath and Foundation Models
27:05 Introduction to Image Repositories
28:36 Using PubMed for Research
30:35 Exploring Undermined Tool
35:42 Comparing PubMed and Undermined
41:00 Final Thoughts and Recommendations


TODAY'S ABSTRACTS & RESOURCES

📄 Here are the abstracts reviewed today:

• A visual-language foundation model for computational pathology 
• A foundation model for clinical-grade computational pathology and rare cancers detection 

▶️ Hamid Tizhoosh's lecture:

•  "Foundation Models and Information retrieval in Pathology"

🔧 The tool we tried today

• Undermind (for literature research)

📕 A book we discussed :)

• "ABC of Artificial Intelligence. Baby University" 

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