J Am Med Inform Assoc - Exploiting domain information for Word Sense Disambiguation of medical documents.

Tópicos

{ extract(1171) text(1153) clinic(932) }
{ method(2212) result(1239) propos(1039) }
{ use(976) code(926) identifi(902) }
{ record(1888) medic(1808) patient(1693) }
{ ehr(2073) health(1662) electron(1139) }
{ data(3008) multipl(1320) sourc(1022) }
{ featur(1941) imag(1645) propos(1176) }
{ system(1050) medic(1026) inform(1018) }
{ research(1218) medic(880) student(794) }
{ framework(1458) process(801) describ(734) }
{ compound(1573) activ(1297) structur(1058) }
{ take(945) account(800) differ(722) }
{ error(1145) method(1030) estim(1020) }
{ method(1557) propos(1049) approach(1037) }
{ control(1307) perform(991) simul(935) }
{ care(1570) inform(1187) nurs(1089) }
{ perform(1367) use(1326) method(1137) }
{ group(2977) signific(1463) compar(1072) }
{ high(1669) rate(1365) level(1280) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ assess(1506) score(1403) qualiti(1306) }
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{ can(981) present(881) function(850) }
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{ studi(1119) effect(1106) posit(819) }
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{ health(3367) inform(1360) care(1135) }
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{ state(1844) use(1261) util(961) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ sampl(1606) size(1419) use(1276) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
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{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

JECTIVE: Current techniques for knowledge-based Word Sense Disambiguation (WSD) of ambiguous biomedical terms rely on relations in the Unified Medical Language System Metathesaurus but do not take into account the domain of the target documents. The authors' goal is to improve these methods by using information about the topic of the document in which the ambiguous term appears.DESIGN: The authors proposed and implemented several methods to extract lists of key terms associated with Medical Subject Heading terms. These key terms are used to represent the document topic in a knowledge-based WSD system. They are applied both alone and in combination with local context.MEASUREMENTS: A standard measure of accuracy was calculated over the set of target words in the widely used National Library of Medicine WSD dataset.RESULTS AND DISCUSSION: The authors report a significant improvement when combining those key terms with local context, showing that domain information improves the results of a WSD system based on the Unified Medical Language System Metathesaurus alone. The best results were obtained using key terms obtained by relevance feedback and weighted by inverse document frequency.

Resumo Limpo

jectiv current techniqu knowledgebas word sens disambigu wsd ambigu biomed term reli relat unifi medic languag system metathesaurus take account domain target document author goal improv method use inform topic document ambigu term appearsdesign author propos implement sever method extract list key term associ medic subject head term key term use repres document topic knowledgebas wsd system appli alon combin local contextmeasur standard measur accuraci calcul set target word wide use nation librari medicin wsd datasetresult discuss author report signific improv combin key term local context show domain inform improv result wsd system base unifi medic languag system metathesaurus alon best result obtain use key term obtain relev feedback weight invers document frequenc

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