EPISODE · Apr 6, 2026 · 40 MIN
222: From Slides to Survival: Can AI Close the Gap?
from Digital Pathology Podcast · host Aleksandra Zuraw, DVM, PhD
Send us Fan MailHow close is pathology AI to making decisions that matter in real workflows, real trials, and real patient care?In this episode of DigiPath Digest, I review five recent papers that approach that question from very different angles. We look at multimodal survival prediction in cervical cancer, pathology-driven response assessment in neoadjuvant immunotherapy for head and neck squamous cell carcinoma, AI-assisted Ki-67 scoring in pulmonary neuroendocrine neoplasms, automation and AI in hematologic diagnostics, and AI-based qFibrosis readouts from the Phase 3 MAESTRO-NASH trial.What I liked about this set of papers is that they do not all tell the same story. Some show clear progress. Some show where AI already works well as an adjunct. Others make it very clear that validation, governance, reproducibility, and workflow design still matter just as much as model performance.Key topics and timestamps00:00 Introduction, Easter edition, and community updates 00:51 USCAP recap, signed book giveaway, and free Digital Pathology 101 PDF 02:04 Partnerships, lab automation preview, and what’s coming in this episode 03:25 Multimodal deep learning for cervical cancer survival prediction 13:00 Why pathology may be a better response endpoint than radiology in neoadjuvant HNSCC immunotherapy 23:09 Ki-67 scoring in pulmonary neuroendocrine neoplasms: pathologists vs two AI systems 33:46 AI, digital morphology, and automation in hematologic diagnostics 43:29 qFibrosis, digital biomarkers, and the MAESTRO-NASH Phase 3 trial 51:57 Closing thoughts, community updates, and Easter promotion Resources Deep Learning Can Predict the Overall Survival of Cervical Cancer Based on Histopathological Image, Gene Mutation and Clinical Information https://pubmed.ncbi.nlm.nih.gov/41902378/ Modern Pathology-Driven Strategies in Neoadjuvant Immunotherapy for Head and Neck Squamous Cell Carcinoma: From Residual Tumor Quantification to Spatial and AI-Based Biomarkers https://pubmed.ncbi.nlm.nih.gov/41899621/ Ki-67 Proliferation Index in Pulmonary Neuroendocrine Neoplasms: Interobserver Agreement Among Pathologists and Comparison of Two Artificial Intelligence-Based Image Analysis Systems https://pubmed.ncbi.nlm.nih.gov/41898274/ Molecular Pathology, Artificial Intelligence, and New Technologies in Hematologic Diagnostics: Translational Opportunities and Practical Considerations https://pubmed.ncbi.nlm.nih.gov/41897649/ Quantitative regression of qFibrosis with resmetirom: Exploratory histologic endpoints from the MAESTRO-NASH phase III clinical trial https://pubmed.ncbi.nlm.nih.gov/41895606/Support the showGet the "Digital Pathology 101" FREE E-book and join us!
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Send us Fan Mail How close is pathology AI to making decisions that matter in real workflows, real trials, and real patient care? In this episode of DigiPath Digest, I review five recent papers that approach that question from very different angles. We look at multimodal survival prediction in cervical cancer, pathology-driven response assessment in neoadjuvant immunotherapy for head and neck squamous cell carcinoma, AI-assisted Ki-67 scoring in pulmonary neuroendocrine neoplasms, automation ...
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222: From Slides to Survival: Can AI Close the Gap?
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