Inform Health Soc Care - Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

Tópicos

{ concept(1167) ontolog(924) domain(897) }
{ framework(1458) process(801) describ(734) }
{ data(1737) use(1416) pattern(1282) }
{ control(1307) perform(991) simul(935) }
{ ehr(2073) health(1662) electron(1139) }
{ can(981) present(881) function(850) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ import(1318) role(1303) understand(862) }
{ implement(1333) system(1263) develop(1122) }
{ process(1125) use(805) approach(778) }
{ sequenc(1873) structur(1644) protein(1328) }
{ imag(2830) propos(1344) filter(1198) }
{ data(1714) softwar(1251) tool(1186) }
{ general(901) number(790) one(736) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ spatial(1525) area(1432) region(1030) }
{ can(774) often(719) complex(702) }
{ method(1219) similar(1157) match(930) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ learn(2355) train(1041) set(1003) }
{ algorithm(1844) comput(1787) effici(935) }
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{ signal(2180) analysi(812) frequenc(800) }
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{ imag(1057) registr(996) error(939) }
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{ featur(3375) classif(2383) classifi(1994) }
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{ take(945) account(800) differ(722) }
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{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
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{ error(1145) method(1030) estim(1020) }
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{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ design(1359) user(1324) use(1319) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
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{ data(3963) clinic(1234) research(1004) }
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{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
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{ visual(1396) interact(850) tool(830) }
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{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ 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) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ estim(2440) model(1874) function(577) }
{ 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

A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

Resumo Limpo

larg amount biomed genom data current avail internet howev data distribut heterogen biolog inform sourc littl even organ semant technolog provid consist reliabl basi confront challeng involv organ manipul visual data knowledg one knowledg represent techniqu use semant process ontolog common defin formal explicit specif share conceptu domain interest work present introduc set interoper algorithm can use domain ontolog inform improv informationretriev process work present ontologybas informationretriev system biomed domain system experi carri describ paper base use domain ontolog creation normal lightweight ontolog repres user prefer determin domain order improv informationretriev process

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