A novel machine learning program applied to discover otological diagnoses.
A novel machine learning system, Galactica, has been developed for knowledge discovery from databases. This system was applied to discover diagnostic rules from a patient database containing 564 cases with vestibular schwannoma, bening paroxysmal positional vertigo, Ménière's disease, sudden deafness, traumatic vertigo and vestibular neuritis diagnoses. The rules were evaluated using an independent testing set. The accuracy of rules for these diagnoses were 91%, 96%, 81%, 95%, 92% and 98%, respectively. Besides being accurate, the rules contained the five most important diagnostic questions identified in the earlier research. The knowledge presented with rules can be easily comprehended and verified.
Laurikkala
J P
JP
Department of Computer Science, University of Tampere, Finland. Jorma.Laurikkala@cs.uta.fi
Kentala
E L
EL
Juhola
M
M
Pyvkkö
I V
IV
D004427:Ear Diseases / Q000175:diagnosis*; D005103:Expert Systems; D006801:Humans; D007858:Learning; D012720:Severity of Illness Index