Methods Inf Med - Citation analysis in health care sciences. Innovative investigation or seductive pseudo-science?

Tópicos

{ research(1085) discuss(1038) issu(1018) }
{ health(1844) social(1437) communiti(874) }
{ research(1218) medic(880) student(794) }
{ studi(2440) review(1878) systemat(933) }
{ studi(1410) differ(1259) use(1210) }
{ ehr(2073) health(1662) electron(1139) }
{ model(3404) distribut(989) bayesian(671) }
{ learn(2355) train(1041) set(1003) }
{ activ(1138) subject(705) human(624) }
{ can(774) often(719) complex(702) }
{ algorithm(1844) comput(1787) effici(935) }
{ search(2224) databas(1162) retriev(909) }
{ howev(809) still(633) remain(590) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ can(981) present(881) function(850) }
{ use(976) code(926) identifi(902) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ method(1219) similar(1157) match(930) }
{ network(2748) neural(1063) input(814) }
{ treatment(1704) effect(941) patient(846) }
{ error(1145) method(1030) estim(1020) }
{ model(2220) cell(1177) simul(1124) }
{ state(1844) use(1261) util(961) }
{ implement(1333) system(1263) develop(1122) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ chang(1828) time(1643) increas(1301) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ 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) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ patient(2837) hospit(1953) medic(668) }
{ 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) }
{ 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) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ 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

CKGROUND: Citations of scientific papers in health care have become a subject of interest, as in any scientific sector. However, such a metric, while useful in a simple way, can become subject to too much credibility, and therefore to advanced analyses which are not soundly grounded even if methodologically valid.OBJECTIVES: The objective was to contextualise citation indices in health care science, juxtaposed with a parallel analytic paper.METHODS: The literature was reviewed and set against the objectives of metrics of literature and of researchers.RESULTS: The strengths and weaknesses of citation indices in the health sector were identified, with practical examples of perverse effects, and compared with the core objectives of health care development.CONCLUSIONS: Citation indices in health care science have a value, but this is limited to giving a broad overview. Other measures of effectiveness, including impact on education, on health care development, and on stimulation of applied developments, are needed rather than spuriously scientific advanced analyses of citation counts.

Resumo Limpo

ckground citat scientif paper health care becom subject interest scientif sector howev metric use simpl way can becom subject much credibl therefor advanc analys sound ground even methodolog validobject object contextualis citat indic health care scienc juxtapos parallel analyt papermethod literatur review set object metric literatur researchersresult strength weak citat indic health sector identifi practic exampl pervers effect compar core object health care developmentconclus citat indic health care scienc valu limit give broad overview measur effect includ impact educ health care develop stimul appli develop need rather spurious scientif advanc analys citat count

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