Table 6

Comparison on AImed. (P)recision, (R)ecall, (F)-score and AUC results for methods evaluated on AImed with the correct cross-validation methodology. Note that the best performing method, introduced by Miwa et al. [34], also utilizes the all-paths graph kernel.

P

R

F

AUC

Miwa et al. [34]

-

-

63.5%

87.9%

Miyao et al. [35]

54.9%

65.5%

59.5%

-

Giuliano et al. [28]

60.9%

57.2%

59.0%

-

All-paths graph kernel

52.9%

61.8%

56.4%

84.8%

Sætre et al. [32]

64.3%

44.1%

52.0%

-

Mitsumori et al. [39]

54.2%

42.6%

47.7%

-

Van Landeghem et al. [29]

49%

44%

46%

-

Yakushiji et al. [40]

33.7%

33.1%

33.4%

-

Airola et al. BMC Bioinformatics 2008 9(Suppl 11):S2   doi:10.1186/1471-2105-9-S11-S2