PANDIA: Ablation Study Results for Infant Pain Assessment AI

Oussama El Othmani published ablation study results for the PANDIA AI system on May 26, 2026. The system was evaluated on 2,847 infants across four datasets, achieving 87.3% accuracy and a 12.4% improvement over baselines. All code, trained models, and preprocessing pipelines are publicly available.

Use Cases

• Benchmarking multimodal AI architectures based on the described hierarchical representation learning and graph-based fusion
• Evaluating federated learning frameworks for privacy-preserving multi-site collaboration in medical AI
• Analyzing concept-bottleneck models for clinical interpretability based on the symbolic reasoning approach
• Testing meta-learning adaptation for personalized assessment with minimal per-patient data

Strengths

• Results are based on evaluation across 2,847 infants
• The system achieved a 92.1% clinician acceptance rate for explanations
• The model maintains fewer than 30M parameters, suitable for edge deployment

Limitations

• The validation design is retrospective, as noted in the description
• Dataset heterogeneity across collection sites is a stated limitation
• Column-level documentation is absent; field semantics must be inferred after download

Provenance

Source

figshare

Freshness

Last updated 2026-05-26 17:32:04