Int J Comput Assist Radiol Surg - Computer-aided simple triage.

Tópicos

{ case(1353) use(1143) diagnosi(1136) }
{ imag(1057) registr(996) error(939) }
{ import(1318) role(1303) understand(862) }
{ time(1939) patient(1703) rate(768) }
{ detect(2391) sensit(1101) algorithm(908) }
{ research(1218) medic(880) student(794) }
{ structur(1116) can(940) graph(676) }
{ activ(1452) weight(1219) physic(1104) }
{ visual(1396) interact(850) tool(830) }
{ age(1611) year(1155) adult(843) }
{ howev(809) still(633) remain(590) }
{ state(1844) use(1261) util(961) }
{ patient(2837) hospit(1953) medic(668) }
{ first(2504) two(1366) second(1323) }
{ can(774) often(719) complex(702) }
{ featur(3375) classif(2383) classifi(1994) }
{ network(2748) neural(1063) input(814) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ chang(1828) time(1643) increas(1301) }
{ clinic(1479) use(1117) guidelin(835) }
{ control(1307) perform(991) simul(935) }
{ search(2224) databas(1162) retriev(909) }
{ studi(1410) differ(1259) use(1210) }
{ research(1085) discuss(1038) issu(1018) }
{ use(2086) technolog(871) perceiv(783) }
{ method(1969) cluster(1462) data(1082) }
{ imag(2675) segment(2577) method(1081) }
{ studi(2440) review(1878) systemat(933) }
{ framework(1458) process(801) describ(734) }
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{ learn(2355) train(1041) set(1003) }
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{ perform(1367) use(1326) method(1137) }
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{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
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{ ehr(2073) health(1662) electron(1139) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ health(1844) social(1437) communiti(874) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ estim(2440) model(1874) function(577) }
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Resumo

RPOSE: Computer-aided detection (CAD) established its role in medical imaging as second reader aimed to boost the diagnostic accuracy of human interpreter. As the diagnostic performance of CAD systems improves and more imaging modalities are covered, CAD steps forward to fill new, more demanding positions in medical practice. In this paper, we investigate how the introduction of CAD for emergency diagnostic imaging shifts the use case paradigm from second reader to initial interpreter and triage tool.METHODS: We start from extracting common characteristics of exiting CAD systems and compare them to those for emergency diagnostic imaging modalities. Based on the deduced requirements, we define a new class of CAD systems-Computer-aided simple triage (CAST) and explore its properties, use case scenarios and clinical benefits. We also discuss the differences between the CAST, CAD, and automated computer diagnosis.RESULTS: A CAST system should serve as a simple triage tool performing a fully automatic analysis and providing initial classification at "per study" level. Positive studies are then immediately analyzed by expert reader, thus reducing delay for patients with critical conditions, while negative studies can be initially dealt with by less experienced staff. Automatic image quality and study complexity assessment can serve as reading prioritization key. CAST system should exhibit sufficiently high specificity, while not compromising the high sensitivity per study.CONCLUSIONS: CAST systems have a potential to become an "enabling technology" allowing introduction of advanced imaging techniques into the emergency workflow protocols by addressing the reader unavailability and reading prioritization problems.

Resumo Limpo

rpose computeraid detect cad establish role medic imag second reader aim boost diagnost accuraci human interpret diagnost perform cad system improv imag modal cover cad step forward fill new demand posit medic practic paper investig introduct cad emerg diagnost imag shift use case paradigm second reader initi interpret triag toolmethod start extract common characterist exit cad system compar emerg diagnost imag modal base deduc requir defin new class cad systemscomputeraid simpl triag cast explor properti use case scenario clinic benefit also discuss differ cast cad autom comput diagnosisresult cast system serv simpl triag tool perform fulli automat analysi provid initi classif per studi level posit studi immedi analyz expert reader thus reduc delay patient critic condit negat studi can initi dealt less experienc staff automat imag qualiti studi complex assess can serv read priorit key cast system exhibit suffici high specif compromis high sensit per studyconclus cast system potenti becom enabl technolog allow introduct advanc imag techniqu emerg workflow protocol address reader unavail read priorit problem

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