ALPaCA: Adapting Llama for Pathology Context Analysis to enable slide-level question answering

Abstract excerpt

Large Vision Language Models (LVLMs) have recently revolutionized computational pathology. LVLMs transform pathology image embeddings into tokens recognizable by large language models, facilitating zero-shot image classification, description generation, question answering, and interactive diagnostics. In clinical practice, pathological assessments often require the analysis of entire tissue slides, integrating inf...

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• Adenocarcinoma of Lung
• Biomarkers, Tumor
• Deep Learning
• ErbB Receptors
• Lung Neoplasms
• Mutation
• Predictive Learning Models
• ROC Curve

Identifiers and source

Literature Corpus work

d6e5e1e2-6b18-5fd3-bb9d-2426f45ee3a1

DOI

10.1101/2025.04.22.25326190