AMIA Annu Symp Proc - Optimizing the txt2MEDLINE search portal for low-resource clinical decision support.

Tópicos

{ search(2224) databas(1162) retriev(909) }
{ patient(2837) hospit(1953) medic(668) }
{ care(1570) inform(1187) nurs(1089) }
{ result(1111) use(1088) new(759) }
{ inform(2794) health(2639) internet(1427) }
{ assess(1506) score(1403) qualiti(1306) }
{ perform(1367) use(1326) method(1137) }
{ health(3367) inform(1360) care(1135) }
{ activ(1138) subject(705) human(624) }
{ health(1844) social(1437) communiti(874) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ featur(3375) classif(2383) classifi(1994) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ problem(2511) optim(1539) algorithm(950) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ clinic(1479) use(1117) guidelin(835) }
{ data(1714) softwar(1251) tool(1186) }
{ method(984) reconstruct(947) comput(926) }
{ perform(999) metric(946) measur(919) }
{ compound(1573) activ(1297) structur(1058) }
{ spatial(1525) area(1432) region(1030) }
{ medic(1828) order(1363) alert(1069) }
{ patient(1821) servic(1111) care(1106) }
{ analysi(2126) use(1163) compon(1037) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ activ(1452) weight(1219) physic(1104) }
{ method(2212) result(1239) propos(1039) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ system(1976) rule(880) can(841) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ motion(1329) object(1292) video(1091) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ error(1145) method(1030) estim(1020) }
{ concept(1167) ontolog(924) domain(897) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ 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) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ 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) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ 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) }
{ 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

txt2MEDLINE provides access to high-quality medical evidence via text-messaging in settings with inadequate Internet access. We optimized the txt2MEDLINE search technique by parsing queries for MeSH (Medical Subject Heading) terms and searching MEDLINE for articles containing these terms in their titles or abstracts. We compared our results to the existing txt2MEDLINE tool by compiling benchmark queries from low-income and low-middle-income countries, and asking doctors and nurses with practice experience in low-resource areas to evaluate them. The median scores on a 5-point Likert scale were 2.9 for the existing txt2MEDLINE vs. 3.8 for the modified version (p=0.015). This reached our predefined criterion for clinical significance, a difference of 0.5 standard deviations. Improving this technology could improve clinical information resources in the world's most medically underserved communities.

Resumo Limpo

txtmedlin provid access highqual medic evid via textmessag set inadequ internet access optim txtmedlin search techniqu pars queri mesh medic subject head term search medlin articl contain term titl abstract compar result exist txtmedlin tool compil benchmark queri lowincom lowmiddleincom countri ask doctor nurs practic experi lowresourc area evalu median score point likert scale exist txtmedlin vs modifi version p reach predefin criterion clinic signific differ standard deviat improv technolog improv clinic inform resourc world medic underserv communiti

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