A myriad of AI, science, and technology experts explore the real challenges and enormous opportunities facing entrepreneurs who are building the future of health. Raising Health, a podcast by a16z Bio + Health and hosted by Kris Tatiossian and Olivia Webb, dives deep into the heart of biotechnology and healthcare innovation. Join veteran company builders, operators, and investors Vijay Pande, Julie Yoo, Vineeta Agarwala, and Jorge Conde, along with distinguished guests like Mark Cuban, Greg ...
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What if the AI tools we trust for cancer diagnosis are not always correct? This episode of DigiPath Digest takes on the uncomfortable but critical question: can AI “lie” to us—and how do we verify its performance before adopting it in clinical practice?
Highlights:
- [00:02:00] Foundation models in action: Deployment of a fine-tuned pathology foundation model for EGFR biomarker detection in lung cancer—reducing the need for rapid molecular tests by 43%.
- [00:08:41] Bone marrow AI misclassifications: Why automated digital morphology still struggles with consistency across leukemia and lymphoma cases.
- [00:14:45] Lossy DICOM conversion: How file format changes can subtly—but significantly—affect AI model performance.
- [00:21:45] Federated tumor segmentation challenge: Coordinating 32 international institutions to benchmark healthcare AI fairly across diverse datasets.
- [00:27:47] AI in gynecologic cytology: Reviewing AI-driven Pap smear screening—promise, limitations, and why rigorous validation remains essential.
- [00:32:27] Takeaway: Trust but verify—AI tools must be validated before they can support or replace clinical decisions.
Resources from this Episode
- Nature Medicine – Fine-tuned pathology foundation model for lung cancer EGFR biomarker detection.
- Scientific Reports (Germany) – Study on how DICOM conversion impacts AI performance in digital pathology.
- Federated Tumor Segmentation Challenge – Benchmarking AI across 32 global institutions.
- Acta Cytologica – Review on AI in gynecologic cytology and Pap smear screening.
Chapters
1. Introduction to AI reliability concerns (00:00:00)
2. Lung cancer biomarker detection success (00:00:46)
3. AI misclassification in bone marrow analysis (00:06:28)
4. DICOM conversion affecting AI performance (00:11:36)
5. Federated benchmarking across institutions (00:17:14)
6. AI in gynecologic cytology screening (00:21:00)
7. Verify before trust conclusion (00:26:36)
166 episodes