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Table 4 Expression cut-offs from the Kaplan-Meier and from the rules.

From: Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients

Probe set IDa

NB-hypo-IIb

Overallc

Relapse freed

  

Expression cut-offe

Worsef

Expression cut-offe

Worsef

  

Kaplan-Meier

Rulex

Kaplan-Meier

Rulex

Kaplan-Meier

Rulex

Kaplan-Meier

Rulex

1

223172_s_at

107

73

high

high

107

73

high

high

2

200738_s_at

1553

1846

high

high

1553

1846

high

high

3

209446_s_at

69

57

high

high

69

57

high

high

4

226452_at

280

326

high

high

280

326

high

high

5

217356_s_at

706

721

high

high

706

721

high

high

6

236180_at

18

13

hgih

hgih

13

13

high

hgih

7

202022_at

101

131

low

low

138

131

low

low

8

224314_s_at

25

29

high

high

25

29

high

high

9

206686_at

36

26

high

high

36

26

high

high

10

223193_x_at

495

324

high

high

572

324

high

high

11

230630_at

19

23

low

low

35

23

low

low

  1. a Probe sets ID indicates the numerical identified of the probeset.
  2. b NB-hyp-II indicates the list of probe sets of the NB-hypo signature belonging to the rules.
  3. c Overall indicates the survival time between the time of an event or last follow up and the time of diagnosis.
  4. d Relapse free indicates the survival time between the first relapse and the time of diagnosis.
  5. e Expression cut-off indicates the optimal cut-off point of each probe set resulting from the Kaplan-Meier scan and from the rules.
  6. f Worse indicates whether high or low expression of a given probe set is associated to the worse survival. Worse survival are calculated from the Kaplan-Meier curve or from the conditions included into the rules.