Exploring the Future: From Pixels to Patients

A comprehensive overview of the current AI SaMD landscape in digital pathology, highlighting key gaps and opportunities to advance workflow optimization.

Inferred spatial gene expression from H&E images to identify cancer biomarkers, revealing that spatial clusters were predictive of disease-free survival and treatment response.

Explores advances in foundation models for computational pathology (unsupervised, self-supervised learning) and the role of LLMs in report processing through information retrieval.

A very encouraging read that highlights the bottom-up adoption of technology and the proliferation of both enablers and challengers across the healthcare ecosystem.

Introduces MedGemma, a novel suite of medical vision-language foundation models that demonstrate advanced medical understanding and reasoning across images and text.

Presents an overview of emerging AI applications in MedTech, highlighting market growth, regulatory evolution, and strategies for responsible adoption of AI-enabled SaMDs.