IRSANet_IDC v0.1.0 Pretrained Weights (Seed1)

IRSANet_IDC v0.1.0 Pretrained Weights (Seed1)

Model Details

Field	Value
Model	IRSANet_IDC
Parameters	347,775
Modules	124

Weight Details

Field	Value
Experiment	Validation
Run	Run1
Seed	1
Fold	5
Epoch	67
Checkpoint	bestAUROC

Evaluation Details

Field	Value
Dataset	IDC
Test samples	42,637
Evaluated	2026-06-03 06:54
TTA	False

Key Metrics (Threshold = 0.461)

Metric	Test	Val
AUC (ROC)	0.959	0.946
Average Precision	0.910	0.863
F1 Score	0.833	—
Balanced Accuracy	0.897	—
Recall (Sensitivity)	0.924	—

Usage

Reconstruction

from irsanet import load_checkpoint

model, ckpt = load_checkpoint("IRSANet_IDC_seed1_fold5_bestAUROC.pt")

Evaluation

from irsanet import evaluate_model
from irsanet_idc import build_datasets

_,_,test_loader,_,_ = build_datasets([],
    cross_val  = True,
    eval_mode  = True,
    seed       = 1,
)

results = evaluate_model(
    weights     = "IRSANet_IDC_seed1_fold5_bestAUROC.pt",
    test_loader = test_loader,
)

print(results["test_results"])

Including a full visual dashboard:

from irsanet.plotting import plot_eval_panel
from irsanet_idc import build_datasets

_,_,test_loader,_,_ = build_datasets([],
    cross_val  = True,
    eval_mode  = True,
    seed       = 1,
)

results = plot_eval_panel(
    weights     = "IRSANet_IDC_seed1_fold5_bestAUROC.pt",
    test_loader = test_loader,
)

print(results["test_results"])