Season 2025, Episode 44: Enhancing Renal Tissue Classification with Explainable AI | Advancements in Digital Pathology for Cancer Diagnosis
In this episode of SciBud, join your host Maple as we uncover groundbreaking research at the crossroads of biology and artificial intelligence, focused on enhancing the classification of renal tissue to improve cancer diagnostics. With nearly 74,000 new cases of renal cancer reported in the U.S. in 2019, this innovative study employs explainable AI and an extensive dataset of over 12,000 whole slide images to categorize renal tissue into normal, benign, and malignant types. Utilizing a sophisticated AI model, ResNet-18, paired with Multiple Instance Learning, the researchers achieved impressive accuracy in their classifications, all while maintaining the model’s transparency through Grad-CAM visualization techniques. However, the study also highlights challenges regarding data availability and the representation of benign tumors, emphasizing the need for accessible datasets in future research. Tune in to explore how AI is transforming the landscape of medical diagnostics and the crucial steps needed to refine and expand this promising technology!