J Biomed Inform - Managing proposals and evaluations of updates to medical knowledge: theory and applications.

Tópicos

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

Resumo

The process of keeping up-to-date the medical knowledge stored in relational databases is of paramount importance. Since quality and reliability of medical knowledge are essential, in many cases physicians' proposals of updates must undergo experts' evaluation before possibly becoming effective. However, until now no theoretical framework has been provided in order to cope with this phenomenon in a principled and non-ad hoc way. Indeed, such a framework is important not only in the medical domain, but in all Wikipedia-like contexts in which evaluation of update proposals is required. In this paper we propose GPVM (General Proposal Vetting Model), a general model to cope with update proposalevaluation in relational databases. GPVM extends the current theory of temporal relational databases and, in particular, BCDM - Bitemporal Conceptual Data Model - "consensus" model, providing a new data model, new operations to propose and acceptreject updates, and new algebraic operators to query proposals. The properties of GPVM are also studied. In particular, GPVM is a consistent extension of BCDM and it is reducible to it. These properties ensure consistency with most relational temporal database frameworks, facilitating implementation on top of current frameworks and interoperability with previous approaches.

Resumo Limpo

process keep uptod medic knowledg store relat databas paramount import sinc qualiti reliabl medic knowledg essenti mani case physician propos updat must undergo expert evalu possibl becom effect howev now theoret framework provid order cope phenomenon principl nonad hoc way inde framework import medic domain wikipedialik context evalu updat propos requir paper propos gpvm general propos vet model general model cope updat proposalevalu relat databas gpvm extend current theori tempor relat databas particular bcdm bitempor conceptu data model consensus model provid new data model new oper propos acceptreject updat new algebra oper queri propos properti gpvm also studi particular gpvm consist extens bcdm reduc properti ensur consist relat tempor databas framework facilit implement top current framework interoper previous approach

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