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DeepSeeNet
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# Checkpoint Results

## ADVAMD

```text
Task: ADVAMD | endpoint: late_amd | positive_class=1

Metrics
-------
overall_accuracy     0.9658 (0.9628-0.9689)
sensitivity          0.8417 (0.8255-0.8576)
specificity          0.9852 (0.9831-0.9874)
kappa                0.8498 (0.8367-0.8632)
auc                  0.9811 (0.9777-0.9844)

Classifier metrics
------------------
loss                 0.1119
exact_accuracy       0.9658 (0.9628-0.9689)
exact_kappa          0.8498 (0.8367-0.8632)

Confusion matrix (rows=true, cols=pred):
[[11217   168]
 [  282  1499]]

Binary confusion matrix (rows=true, cols=pred):
[[11217   168]
 [  282  1499]]
```

## DRUS

```text
Task: DRUS | endpoint: large_drusen | positive_class=2

Metrics
-------
overall_accuracy     0.8816 (0.8763-0.8869)
sensitivity          0.7708 (0.7588-0.7832)
specificity          0.9368 (0.9319-0.9418)
kappa                0.7263 (0.7144-0.7386)
auc                  0.9489 (0.9452-0.9524)

Classifier metrics
------------------
loss                 0.5903
exact_accuracy       0.7471 (0.7400-0.7542)
exact_kappa          0.6170 (0.6066-0.6280)
macro_ovr_auc        0.8960 (0.8919-0.9001)

Confusion matrix (rows=true, cols=pred):
[[4205  820  115]
 [ 951 2255  440]
 [ 182  822 3376]]

Binary confusion matrix (rows=true, cols=pred):
[[8231  555]
 [1004 3376]]
```

## PIG

```text
Task: PIG | endpoint: pigmentary_abnormality | positive_class=1

Metrics
-------
overall_accuracy     0.8925 (0.8874-0.8976)
sensitivity          0.8606 (0.8502-0.8701)
specificity          0.9113 (0.9053-0.9171)
kappa                0.7702 (0.7594-0.7811)
auc                  0.9498 (0.9460-0.9536)

Classifier metrics
------------------
loss                 0.2734
exact_accuracy       0.8925 (0.8874-0.8976)
exact_kappa          0.7702 (0.7594-0.7811)

Confusion matrix (rows=true, cols=pred):
[[7541  734]
 [ 682 4209]]

Binary confusion matrix (rows=true, cols=pred):
[[7541  734]
 [ 682 4209]]
```