J. Med. Internet Res. - Crowdsourcing knowledge discovery and innovations in medicine.

Tópicos

{ research(1218) medic(880) student(794) }
{ implement(1333) system(1263) develop(1122) }
{ decis(3086) make(1611) patient(1517) }
{ method(1969) cluster(1462) data(1082) }
{ data(1737) use(1416) pattern(1282) }
{ problem(2511) optim(1539) algorithm(950) }
{ group(2977) signific(1463) compar(1072) }
{ health(1844) social(1437) communiti(874) }
{ care(1570) inform(1187) nurs(1089) }
{ perform(999) metric(946) measur(919) }
{ visual(1396) interact(850) tool(830) }
{ process(1125) use(805) approach(778) }
{ imag(1947) propos(1133) code(1026) }
{ imag(2830) propos(1344) filter(1198) }
{ take(945) account(800) differ(722) }
{ design(1359) user(1324) use(1319) }
{ search(2224) databas(1162) retriev(909) }
{ howev(809) still(633) remain(590) }
{ import(1318) role(1303) understand(862) }
{ monitor(1329) mobil(1314) devic(1160) }
{ state(1844) use(1261) util(961) }
{ gene(2352) biolog(1181) express(1162) }
{ survey(1388) particip(1329) question(1065) }
{ system(1976) rule(880) can(841) }
{ network(2748) neural(1063) input(814) }
{ method(1557) propos(1049) approach(1037) }
{ general(901) number(790) one(736) }
{ featur(1941) imag(1645) propos(1176) }
{ model(2341) predict(2261) use(1141) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ health(3367) inform(1360) care(1135) }
{ patient(2837) hospit(1953) medic(668) }
{ medic(1828) order(1363) alert(1069) }
{ drug(1928) target(777) effect(648) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ data(1714) softwar(1251) tool(1186) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ method(984) reconstruct(947) comput(926) }
{ case(1353) use(1143) diagnosi(1136) }
{ 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) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ ehr(2073) health(1662) electron(1139) }
{ 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) }
{ sampl(1606) size(1419) use(1276) }
{ 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) }
{ 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) }
{ result(1111) use(1088) new(759) }
{ estim(2440) model(1874) function(577) }
{ activ(1452) weight(1219) physic(1104) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous and seemingly insolvable questions. But these groups tend to work in isolated environments, and do not communicate or interact effectively. Clinicians are typically buried in the weeds and exigencies of daily practice such that they do not recognize or act on ways to improve knowledge discovery. Researchers may not be able to identify the gaps in clinical knowledge. For data scientists, the main challenge is discerning what is relevant in a domain that is both unfamiliar and complex. Each type of domain expert can contribute skills unavailable to the other groups. "Health hackathons" and "data marathons", in which diverse participants work together, can leverage the current ready availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented, but functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled.

Resumo Limpo

clinician face difficult treatment decis context well address avail evid formul base research digit medicin provid opportun clinician collabor research data scientist solut previous ambigu seem insolv question group tend work isol environ communic interact effect clinician typic buri weed exig daili practic recogn act way improv knowledg discoveri research may abl identifi gap clinic knowledg data scientist main challeng discern relev domain unfamiliar complex type domain expert can contribut skill unavail group health hackathon data marathon divers particip work togeth can leverag current readi avail digit data discov new knowledg util complementari skill expertis talent function divid group innov formul system level result knowledg discoveri process simultan democrat improv real problem solv crossdisciplinari collabor support innov enabl

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