• This is malignancy classification using simple deep learning method in LIDC-IDRI dataset.

• Malignancy (True): 633, Benign (False): 1992

• The dataset can download the below link.

  -> Dataset (LIDC-IDRI) : https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=1966254

• Contact

  -> giseg2118@gmail.com

The code is based on

• torch == '2.0.0'
• timm == '0.6.12'
• pylidc == '0.2.3'
• torchmetrics == '0.9.3'
• sklean == '1.0.2'
• kornia == '0.6.8'

<ROC analysis>

Acc: 81.09, Balenced Acc.:75.21, spec.:0.8109, pre.:0.7964, rec.:0.8109, F1: 0.7957 ROC AUC: 0.7671, PR AUC: 0.8106

Confusion matrix

	False	True
False	557	41
True	108	82

Analysis #1

	precision	recall	f1-score	support
False	0.8376	0.9314	0.8820	598
True	0.6667	0.4316	0.5240	190
accuracy			0.8109	788
macro avg	0.7521	0.6815	0.7030	788
weighted avg	0.7964	0.8109	0.7957	788

Analysis #2

	Sensitivity	Specificity	Precision	ACC
False	0.931438	0.431579	0.837594	0.810914
True	0.431579	0.931438	0.666667	0.810914