Table 20 Sample from dataframe generated from CAD tag time predictions.

From: Heart disease risk factors detection from electronic health records using advanced NLP and deep learning techniques

SentenceID

Sentence

Label

File

Class0

Class1

Class2

Class3

predClass

predLabel

8

HPI: 70 yo M with NIDDM admitted for cath aft.

Before DCT

110-03.xml

0.999235

0.000022

0.000710

0.000033

Class0

Other

12

MIBI was read as positive for moderate to seve.

Before DCT

110-03.xml

0.995930

0.000060

0.003940

0.000071

Class0

Other

60

The ECG is positive for ischemia.

Before DCT

110-03.xml

0.985374

0.000127

0.014360

0.000139

Class0

Other

62

Findings are consistent with moderate to sever.

Before DCT

110-03.xml

0.999231

0.000032

0.000698

0.000039

Class0

Other

68

\tIschemia: Hx angina, MIBI positive for infer.

Before DCT

110-03.xml

0.999664

0.000042

0.000254

0.000040

Class0

Other

94

The pain does not remind him of his sx prior t.

Before DCT

110-04.xml

0.804428

0.000567

0.194260

0.000744

Class0

Other

182

walking, took 2 nitro and the pain got better.

Before DCT

111-04.xml

0.999683

0.000022

0.000273

0.000022

Class0

Other

184

repeat episode relived by nitro again.

Before DCT

111-04.xml

0.999844

0.000016

0.000124

0.000016

Class0

Other

198

PAST SURGICAL HISTORY: Angioplasty with multi.

Before DCT

111-04.xml

0.802693

0.000435

0.196281

0.000591

Class0

Other

257

He tells me that he underwent testing at Wheat.

Before DCT

112-03.xml

0.997462

0.000051

0.002432

0.000056

Class0

Other