Recognizing new medical knowledge computationally.
Can new medical knowledge be recognized computationally? We know knowledge is changing, and our knowledge-based systems will need to accommodate that change in knowledge on a regular basis if they are to stay successful. Computational recognition of these changes seems desirable. It is unlikely that low level objects in the computational universe, bits and characters, will change much over time, higher level objects of language, where meaning begins to emerge, may show change. An analysis of ten arbitrarily selected paragraphs from the Medical Knowledge Self-Assessment Program of the American College of Physicians was used as a test bed for nominal phrase recognition. While there were words not known to Meta-1.2, only 8 of the 32 concepts new to the primary author were pointed to by new words. Use of a barrier word method was successful in identifying 23 of the 32 new concepts. Use of co-occurrence (in sentences) of putative nominal phrases may reduce the amount of human effort involved in recognizing the emergence of new relationships.
Nelson
S J
SJ
Department of Internal Medicine, Medical College of Georgia, Augusta.
Cole
W G
WG
Tuttle
M S
MS
Olson
N E
NE
Sherertz
D D
DD
D001185:Artificial Intelligence; D006801:Humans; D007802:Language; D009626:Terminology as Topic; D017432:Unified Medical Language System