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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, Me´nie`re’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. [ABSTRACT FROM AUTHOR]

The article presents information on the infectious etiology of acute otitis media (AOM), based on a prospective case series that used needle tympanocentesis in children in the U.S., Turkey, Finland and Scandinavia. The case series reveal higher bacterial pathogens were isolated than were virus in study participants. Recommendations from the American Academy of Pediatrics and the American Academy of Physicians that are related to children with AOM are offered.