Clinical Model Validation
Model Version: CNN-2026-02-18 | Dataset N=656
Overall correct diagnoses across 656 test samples.
Total Accuracy
86%
Reliability: The weighted average precision across all categories.
Precision (Avg)
0.86
Sensitivity: The weighted average recall across all categories.
Recall (Avg)
0.86
The harmonic mean of Precision and Recall.
F1-Score (Avg)
0.86
Class-Specific Sensitivity (Recall)
Critical Confusion Insight
Evaluation identifies Glioma (70% recall) as the primary clinical challenge. The Confusion Matrix reveals 45 Gliomas were misclassified as Meningiomas.
Recommendation
Implement multi-view T1/T2 weighted analysis to improve Glioma differentiation.
Statistical Convergence
Training History
History indicates high validation volatility; fetched from secure Cloudinary storage.
Diagnostic Confusion Map
N=656 Matrix
Diagonal intensity confirms correct identifications; externalized for optimized deployment.