J Med Syst - Towards the systematic development of medical networking technology.

Tópicos

{ patient(1821) servic(1111) care(1106) }
{ monitor(1329) mobil(1314) devic(1160) }
{ implement(1333) system(1263) develop(1122) }
{ process(1125) use(805) approach(778) }
{ inform(2794) health(2639) internet(1427) }
{ use(2086) technolog(871) perceiv(783) }
{ case(1353) use(1143) diagnosi(1136) }
{ health(3367) inform(1360) care(1135) }
{ gene(2352) biolog(1181) express(1162) }
{ framework(1458) process(801) describ(734) }
{ chang(1828) time(1643) increas(1301) }
{ data(1714) softwar(1251) tool(1186) }
{ system(1050) medic(1026) inform(1018) }
{ patient(2837) hospit(1953) medic(668) }
{ cost(1906) reduc(1198) effect(832) }
{ can(774) often(719) complex(702) }
{ system(1976) rule(880) can(841) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ problem(2511) optim(1539) algorithm(950) }
{ learn(2355) train(1041) set(1003) }
{ general(901) number(790) one(736) }
{ howev(809) still(633) remain(590) }
{ research(1085) discuss(1038) issu(1018) }
{ state(1844) use(1261) util(961) }
{ signal(2180) analysi(812) frequenc(800) }
{ bind(1733) structur(1185) ligand(1036) }
{ network(2748) neural(1063) input(814) }
{ clinic(1479) use(1117) guidelin(835) }
{ design(1359) user(1324) use(1319) }
{ featur(1941) imag(1645) propos(1176) }
{ import(1318) role(1303) understand(862) }
{ record(1888) medic(1808) patient(1693) }
{ research(1218) medic(880) student(794) }
{ time(1939) patient(1703) rate(768) }
{ high(1669) rate(1365) level(1280) }
{ decis(3086) make(1611) patient(1517) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ 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) }
{ 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) }
{ 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) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ 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) }
{ 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) }
{ medic(1828) order(1363) alert(1069) }
{ group(2977) signific(1463) compar(1072) }
{ 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) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ 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) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }

Resumo

Currently, there is a disparity in the availability of doctors between urban and rural areas of developing countries. Most experienced doctors and specialists, as well as advanced diagnostic technologies, are available in urban areas. People living in rural areas have less or sometimes even no access to affordable healthcare facilities. Increasing the number of doctors and charitable medical hospitals or deploying advanced medical technologies in these areas might not be economically feasible, especially in developing countries. We need to mobilize science and technology to master this complex, large scale problem in an objective, logical, and professional way. This can only be achieved with a collaborative effort where a team of experts works on both technical and non-technical aspects of this health care divide. In this paper we use a systems engineering framework to discuss hospital networks which might be solution for the problem. We argue that with the advancement in communication and networking technologies, economically middle class people and even some rural poor have access to internet and mobile communication systems. Thus, Hospital Digital Networking Technologies (HDNT), such as telemedicine, can be developed to utilize internet, mobile and satellite communication systems to connect primitive rural healthcare centers to well advanced modern urban setups and thereby provide better consultation and diagnostic care to the needy people. This paper describes requirements and limitations of the HDNTs. It also presents the features of telemedicine, the implementation issues and the application of wireless technologies in the field of medical networking.

Resumo Limpo

current dispar avail doctor urban rural area develop countri experienc doctor specialist well advanc diagnost technolog avail urban area peopl live rural area less sometim even access afford healthcar facil increas number doctor charit medic hospit deploy advanc medic technolog area might econom feasibl especi develop countri need mobil scienc technolog master complex larg scale problem object logic profession way can achiev collabor effort team expert work technic nontechn aspect health care divid paper use system engin framework discuss hospit network might solut problem argu advanc communic network technolog econom middl class peopl even rural poor access internet mobil communic system thus hospit digit network technolog hdnt telemedicin can develop util internet mobil satellit communic system connect primit rural healthcar center well advanc modern urban setup therebi provid better consult diagnost care needi peopl paper describ requir limit hdnts also present featur telemedicin implement issu applic wireless technolog field medic network

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