J Biomed Inform - BOAT: automatic alignment of biomedical ontologies using term informativeness and candidate selection.

Tópicos

{ concept(1167) ontolog(924) domain(897) }
{ sequenc(1873) structur(1644) protein(1328) }
{ use(976) code(926) identifi(902) }
{ design(1359) user(1324) use(1319) }
{ howev(809) still(633) remain(590) }
{ take(945) account(800) differ(722) }
{ high(1669) rate(1365) level(1280) }
{ featur(3375) classif(2383) classifi(1994) }
{ can(981) present(881) function(850) }
{ imag(1947) propos(1133) code(1026) }
{ learn(2355) train(1041) set(1003) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ search(2224) databas(1162) retriev(909) }
{ perform(999) metric(946) measur(919) }
{ studi(1119) effect(1106) posit(819) }
{ sampl(1606) size(1419) use(1276) }
{ decis(3086) make(1611) patient(1517) }
{ method(1219) similar(1157) match(930) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ problem(2511) optim(1539) algorithm(950) }
{ control(1307) perform(991) simul(935) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ research(1085) discuss(1038) issu(1018) }
{ perform(1367) use(1326) method(1137) }
{ health(3367) inform(1360) care(1135) }
{ data(2317) use(1299) case(1017) }
{ signal(2180) analysi(812) frequenc(800) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ analysi(2126) use(1163) compon(1037) }
{ drug(1928) target(777) effect(648) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ framework(1458) process(801) describ(734) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ clinic(1479) use(1117) guidelin(835) }
{ data(1714) softwar(1251) tool(1186) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ 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) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The biomedical sciences is one of the few domains where ontologies are widely being developed to facilitate information retrieval and knowledge sharing, but there still remains the problem that applications using different ontologies cannot share knowledge without explicit references between overlapping concepts. Ontology alignment is the task of identifying such equivalence relations between concepts across ontologies. Its application to the biomedical domain should address two open issues: (1) determining the equivalence of concept-pairs which have overlapping terms in their names, and (2) the high run-time required to align large ontologies which are typical in the biomedical domain. To address them, we present a novel approach, named the Biomedical Ontologies Alignment Technique (BOAT), which is state-of-the-art in terms of F-measure, precision and speed. A key feature of BOAT is that it considers the informativeness of each component word in the concept labels, which has significant impact on biomedical ontologies, resulting in a 12.2% increase in F-measure. Another important feature of BOAT is that it selects for comparison only concept pairs that show high likelihoods of equivalence, based on the similarity of their annotations. BOAT's F-measure of 0.88 for the alignment of the mouse and human anatomy ontologies is on par with that of another state-of-the-art matcher, AgreementMaker, while taking a shorter time.

Resumo Limpo

biomed scienc one domain ontolog wide develop facilit inform retriev knowledg share still remain problem applic use differ ontolog share knowledg without explicit refer overlap concept ontolog align task identifi equival relat concept across ontolog applic biomed domain address two open issu determin equival conceptpair overlap term name high runtim requir align larg ontolog typic biomed domain address present novel approach name biomed ontolog align techniqu boat stateoftheart term fmeasur precis speed key featur boat consid inform compon word concept label signific impact biomed ontolog result increas fmeasur anoth import featur boat select comparison concept pair show high likelihood equival base similar annot boat fmeasur align mous human anatomi ontolog par anoth stateoftheart matcher agreementmak take shorter time

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