This week on How I AI, I am joined by Dr. Akash Parvatikar, a computational pathologist and medical imaging scientist who works at the intersection of AI and healthcare.
Akash earned his Ph.D. through the joint Carnegie Mellon–University of Pittsburgh School of Medicine in Computational Biology and has been developing advanced AI workflows that support doctors in analyzing medical images and improving diagnostic accuracy.
We explore how large language models (LLMs), Python, and agentic workflows are being used in modern medical imaging labs, the move toward digital pathology, and the new possibilities that come with remote collaboration and telepathology. This episode offers a behind-the-scenes look at how scientists are approaching AI adoption in ways that are practical, regulated, and patient‑focused.
🔥 Topics We Cover
- How computational pathology is shaping the future of medical imaging
- The shift from physical slides to digital workflows in pathology
- How AI tools assist specialists by streamlining repetitive image analysis
- Agentic workflows and why they are not just for large language models
- The role of telepathology in connecting specialists globally
🛠️ AI Tools and Workflow Akash Mentions
- Python for building AI scripts
- NumPy for numerical computing
- Scikit-learn for machine learning tasks
- LLMs and agentic workflows for diagnostics
- Digital pathology platforms for slide digitization and quality review
📲 Connect with Dr. Akash Parvatikar
🎧 If you enjoyed this episode, please leave a review and share it with a friend working in healthcare, AI, or life sciences. How I AI is here to spotlight the quiet builders and brilliant minds using artificial intelligence to elevate real human impact.
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