Evaluating Cell AI Foundation Models in Kidney Pathology with Human-in-the-Loop Enrichment

arXiv:2411.00078 · cs.CV, cs.AI, eess.IV · Submitted 2024-10-31 · Read on arXiv

cs.CV, cs.AI, eess.IV

Submitted: 2024-10-31

Updated: 2025-11-09

Code: https://github.com/hrlblab/AFM_

Terminology

• Foundation Model — 99× in this paper · explained in 3 episodes
• Foundation Models — 73× in this paper · explained in 7 episodes
• Fine-Tuning — 41× in this paper · explained in 5 episodes
• Instance Segmentation — 20× in this paper · explained in 3 episodes
• F1 Score — 17× in this paper · explained in 3 episodes
• Human-in-the-Loop — 11× in this paper · explained in 3 episodes
• AI Foundation Model — 8× in this paper · explained in 1 episode
• Pseudo-labels — 8× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Continual Learning — 4× in this paper · explained in 2 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Kidney Precision Medicine Project — 3× in this paper
• National Institutes of Health — 3× in this paper
• Robustness — 3× in this paper · explained in 5 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Foundation Models (FMs) — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Computational Biology — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• National Center for Advancing Translational Sciences — 1× in this paper
• Segment Anything Model (SAM) — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• On the Opportunities and Risks of Foundation Models
• Foundation Models in Computational Pathology: A Review of Challenges, Opportunities, and Impact
• Foundation Models for Biomedical Image Segmentation: A Survey

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