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116: DigiPath Digest #18 | Federated Learning in Pathology. Developing AI Models While Preserving Privacy
Manage episode 454128932 series 3404634
In today's DigiPath Digest, we delve into federated learning, a decentralized approach to AI training that preserves data privacy.
I discuss recent papers from PubMed and share my experiences experimenting with AI tools like Perplexity and Gemini for research efficiency.
You will also get updates on upcoming plans, including leveraging AI to share more podcasts with you.
Did I mention that this is the last livestream of the year as I head to Poland for Christmas? No More DigiPath Digests. We got to number 18 (I overestimated it a bit in the podcast), and you have been instrumental in continuing this series!
Big THANK YOU to all the digital Pathology #TRLBLZRS showing up every Friday morning for this!
Join me as we tackle the nuances of federated learning and its impact on healthcare and pathology.
00:00 Introduction and Greetings
00:18 Today's Topic: Federated Learning
00:57 AI Tools and Updates
04:39 Federated Learning in Detail
08:03 Challenges and Benefits of Federated Learning
11:21 Exploring More Papers and Future Plans
22:53 Wrapping Up and Final Thoughts
Links and Resources:
- Subscribe to Digital Pathology Podcast on YouTube
- Free E-book "Pathology 101"
- YouTube (unedited) version of this episode
- Try Perplexity with my referral link
- My new page built with Perplexity
Publications Discussed Today:
📝 Privacy-preserving federated data access and federated learning: Improved data sharing and AI model development in transfusion medicine
🔗https://pubmed.ncbi.nlm.nih.gov/39610333/
📝 A review on federated learning in computational pathology
🔗https://pubmed.ncbi.nlm.nih.gov/39582895/
If you enjoyed this episode, please subscribe and leave a review on your podcast listening App!
Become a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!
119 에피소드
Manage episode 454128932 series 3404634
In today's DigiPath Digest, we delve into federated learning, a decentralized approach to AI training that preserves data privacy.
I discuss recent papers from PubMed and share my experiences experimenting with AI tools like Perplexity and Gemini for research efficiency.
You will also get updates on upcoming plans, including leveraging AI to share more podcasts with you.
Did I mention that this is the last livestream of the year as I head to Poland for Christmas? No More DigiPath Digests. We got to number 18 (I overestimated it a bit in the podcast), and you have been instrumental in continuing this series!
Big THANK YOU to all the digital Pathology #TRLBLZRS showing up every Friday morning for this!
Join me as we tackle the nuances of federated learning and its impact on healthcare and pathology.
00:00 Introduction and Greetings
00:18 Today's Topic: Federated Learning
00:57 AI Tools and Updates
04:39 Federated Learning in Detail
08:03 Challenges and Benefits of Federated Learning
11:21 Exploring More Papers and Future Plans
22:53 Wrapping Up and Final Thoughts
Links and Resources:
- Subscribe to Digital Pathology Podcast on YouTube
- Free E-book "Pathology 101"
- YouTube (unedited) version of this episode
- Try Perplexity with my referral link
- My new page built with Perplexity
Publications Discussed Today:
📝 Privacy-preserving federated data access and federated learning: Improved data sharing and AI model development in transfusion medicine
🔗https://pubmed.ncbi.nlm.nih.gov/39610333/
📝 A review on federated learning in computational pathology
🔗https://pubmed.ncbi.nlm.nih.gov/39582895/
If you enjoyed this episode, please subscribe and leave a review on your podcast listening App!
Become a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!
119 에피소드
모든 에피소드
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1 118: Why are So Few Pathologists Attending Digital Pathology Conferences 30:51
1 117: Tertiary Lymphoid Structures in Colorectal Cancer Prognosis | Dr. Aleks + AI 22:15
1 116: DigiPath Digest #18 | Federated Learning in Pathology. Developing AI Models While Preserving Privacy 26:33
1 115: Pathology Meets AI: Combining Veterinary and Medical Pathology for Digital Advancements w/ Richard Doughty, DVM, MD, MSc AIFORIA 1:06:06
1 114: Radiology Partners’ approach to clinical AI applications: w/ Nina Kottler, MD, MS, FSIIM | Radiology Partners 54:22
1 113: DigiPath Digest #16 | PathVisions Recap, Ai in Breast Cancer Diagnostics and Global Health 29:29
1 112: AI's GROWING ROLE IN THE FUTURE OF PATHOLOGY W/ Adam Cole and Jason Camilletti 1:13:09
1 111: FDA and LDT's what does it actually mean for the labs? Kitchen chat w/ Dr. Thomas Nifong 21:52
1 110: Can AI Improve Veterinary Diagnostics and Academic Efficiency w/ Candice Chu, DVM, PhD, DACVP, Texas A&M 41:06
1 109: How AI is Transforming Veterinary Diagnostics w/ Richard Fox, DVM, Dipl ECVP | Aiforia 1:03:30
1 108: DigiPath Digest #14 (AI in Pathology: Case Prioritization, Kidney Biopsy Analysis and the Need for Consistent TIL Quantification). 32:40
1 107: DigiPath Digest #13 (Revolutionizing Pathology with AI: Insights from PD-1 to Prostate Cancer Predictions) 23:34
1 106: Blind expert pathology opinions enabled digital pathology help win legal cases w/ Stephanie Franckewitz, JD, MBA 56:03
1 105: Artificial intelligence in pathology Part 1 - the presentation I gave on the day I got engaged. 26:34
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