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How can pathology labs keep up with rising cancer diagnoses when the workforce is shrinking?  Dr. Anil Parwani believes the answer lies in digital pathology powered by AI—and in this episode, he shares how his team at Ohio State University is making it work today.

Amid increasing demands and workforce shortages, pathology is embracing digital transformation. The Ohio State University, for instance, has scanned over 4.2 million slides since 2016, leveraging digital pathology for standardization and objectivity. 

Current AI applications aid in biomarker quantification, rare event detection, and tumor classification, with future innovations expected in virtual staining, 3D pathology, and large language model integration. 

While integration challenges remain, these digital tools are poised to augment, rather than replace, human expertise, allowing each institution to navigate its unique "digital pathology chasm" with available market solutions.

Episode Highlights with Timestamps:

• [00:02:15] From glass slides to digital workflows: why the shift was inevitable.
• [00:05:40] Whole slide imaging: achieving diagnostic quality equal to traditional microscopy.
• [00:12:22] AI in action: biomarker quantification, rare event detection, and tumor classification.
• [00:18:50] The next challenge—integrating AI seamlessly into LIS.
• [00:24:05] Virtual staining and 3D pathology: cutting costs and expanding insights.
• [00:32:10] Large language models: chatbots as diagnostic assistants and education tools.
• [00:39:00] Why human expertise remains irreplaceable in complex cases.
• [00:44:15] Global disparities: how to democratize digital pathology adoption.
• [00:50:30] The future: autonomous AI-assisted diagnostics and precision medicine.
  
  

Resources from this Episode:

• Epredia Digital Pathology: https://www.epredia.com/products/digital-pathology 

Ohio State University Wexner Medical Center: pathology.osu.edu 

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