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Table 2 Summary of reference data - attribute information and distribution

From: Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support

Attribute

Values/Distribution

Description

1

Age

[7 … 78]a

Age of the patient

2

Sex

male(139)b, female(16)

Gender of the patient

3

Steroids

posc (78), neg (76)

A class of medication used to provide relief for inflamed areas of the body

4

Antivirals

pos (131), neg (24)

A class of medication used specifically for treating viral infections

5

Fatigue

pos (54), neg (100)

Extreme tiredness, typically resulting from mental or physical illness

6

Malaise

pos (93), neg (61)

A general feeling of discomfort, illness, or uneasiness

7

Anorexia

pos (122), neg (32)

Eating disorder causing people to obsess about weight and what they eat

8

Big Liver

pos (120), neg (25)

Liver is swollen beyond its normal size

9

Firm Liver

pos (84), neg (60)

Liver tissue is harder than normal

10

Spleen Palpable

pos (120), neg (30)

Spleen becomes touchable or bigger than normal size

11

Spiders

pos (99), neg (51)

Small angiomata which appear on the surface of the skin

12

Ascites

pos (130), neg (20)

Accumulation of fluid in the peritoneal cavity, causing abdominal swelling

13

Varices

pos (132), neg (18)

Abnormal veins in lower part of the tube running from throat to stomach

14

Bilirubin

[0.3 … 8.0]

A yellowish pigment found in bile, a fluid made by the liver

15

Alkaline Phosphate

[26 … 295]

A protein found in all body tissues, including the liver, bile ducts, and bone

16

SGOT

[14 … 648]

One of the enzymes that helps liver build and break down proteins

17

Albumin

[2.1 … 6.4]

The main protein of human blood plasma

18

ProTime INR

[0 … 100]

The test that is used to determine the clotting tendency of blood

19

Histology

pos (70), neg (85)

The study of the microscopic anatomy of cells and tissues

20

Patient Label

die (32), live (123)

Entity label, required for evaluating machine learning systems

  1. arange of attributes with continuous values
  2. bdistribution of attributes with categorical values
  3. cpos: positive, neg: negative
  4. The numeric ranges show the intervals for continuous values
  5. For categorical values, the numbers of patients with/without that attribute are shown