AMIA Annu Symp Proc - Alignment and clustering of breast cancer patients by longitudinal treatment history.

Tópicos

{ cancer(2502) breast(956) screen(824) }
{ method(1969) cluster(1462) data(1082) }
{ method(1219) similar(1157) match(930) }
{ compound(1573) activ(1297) structur(1058) }
{ care(1570) inform(1187) nurs(1089) }
{ data(3963) clinic(1234) research(1004) }
{ network(2748) neural(1063) input(814) }
{ patient(2837) hospit(1953) medic(668) }
{ inform(2794) health(2639) internet(1427) }
{ learn(2355) train(1041) set(1003) }
{ search(2224) databas(1162) retriev(909) }
{ risk(3053) factor(974) diseas(938) }
{ health(3367) inform(1360) care(1135) }
{ data(3008) multipl(1320) sourc(1022) }
{ can(981) present(881) function(850) }
{ health(1844) social(1437) communiti(874) }
{ data(1737) use(1416) pattern(1282) }
{ imag(1057) registr(996) error(939) }
{ featur(3375) classif(2383) classifi(1994) }
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{ perform(1367) use(1326) method(1137) }
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{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
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{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ 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) }
{ group(2977) signific(1463) compar(1072) }
{ gene(2352) biolog(1181) express(1162) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ analysi(2126) use(1163) compon(1037) }
{ high(1669) rate(1365) level(1280) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
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{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Longitudinal treatment histories may offer valuable information about clinical practice patterns to the clinical researcher as part of data exploration, cohort identification, or discovery of potentially beneficial or harmful practices in the health care community. We present a novel approach to temporal clustering of patient treatment information based on the semantic similarity of longitudinal histories. Using combined breast cancer registry data from two neighboring health care institutions, we constructed a database of longitudinal treatment histories that included surgical procedures, radiation therapy, chemotherapy, and hormone replacement therapy. We then did pair-wise similarity comparisons of treatment histories, and used the similarity measures to cluster patients with machine learning methods. An evaluation of our results found that patients clustered on stage of breast cancer and type of treatment provided. We propose that this approach can be applied towards identification of similar cohorts, and for discovery of novel or anomalous clinical practice patterns.

Resumo Limpo

longitudin treatment histori may offer valuabl inform clinic practic pattern clinic research part data explor cohort identif discoveri potenti benefici harm practic health care communiti present novel approach tempor cluster patient treatment inform base semant similar longitudin histori use combin breast cancer registri data two neighbor health care institut construct databas longitudin treatment histori includ surgic procedur radiat therapi chemotherapi hormon replac therapi pairwis similar comparison treatment histori use similar measur cluster patient machin learn method evalu result found patient cluster stage breast cancer type treatment provid propos approach can appli toward identif similar cohort discoveri novel anomal clinic practic pattern

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