Artif Intell Med - Predicting patient survival after liver transplantation using evolutionary multi-objective artificial neural networks.

Tópicos

{ model(2341) predict(2261) use(1141) }
{ error(1145) method(1030) estim(1020) }
{ perform(999) metric(946) measur(919) }
{ estim(2440) model(1874) function(577) }
{ algorithm(1844) comput(1787) effici(935) }
{ control(1307) perform(991) simul(935) }
{ system(1976) rule(880) can(841) }
{ import(1318) role(1303) understand(862) }
{ health(3367) inform(1360) care(1135) }
{ data(3008) multipl(1320) sourc(1022) }
{ can(774) often(719) complex(702) }
{ decis(3086) make(1611) patient(1517) }
{ patient(2837) hospit(1953) medic(668) }
{ first(2504) two(1366) second(1323) }
{ use(976) code(926) identifi(902) }
{ network(2748) neural(1063) input(814) }
{ take(945) account(800) differ(722) }
{ general(901) number(790) one(736) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ data(2317) use(1299) case(1017) }
{ implement(1333) system(1263) develop(1122) }
{ method(2212) result(1239) propos(1039) }
{ imag(1057) registr(996) error(939) }
{ patient(2315) diseas(1263) diabet(1191) }
{ learn(2355) train(1041) set(1003) }
{ featur(1941) imag(1645) propos(1176) }
{ data(3963) clinic(1234) research(1004) }
{ research(1085) discuss(1038) issu(1018) }
{ model(2656) set(1616) predict(1553) }
{ group(2977) signific(1463) compar(1072) }
{ gene(2352) biolog(1181) express(1162) }
{ use(1733) differ(960) four(931) }
{ detect(2391) sensit(1101) algorithm(908) }
{ bind(1733) structur(1185) ligand(1036) }
{ framework(1458) process(801) describ(734) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ model(2220) cell(1177) simul(1124) }
{ method(984) reconstruct(947) comput(926) }
{ howev(809) still(633) remain(590) }
{ visual(1396) interact(850) tool(830) }
{ studi(1119) effect(1106) posit(819) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ signal(2180) analysi(812) frequenc(800) }
{ patient(1821) servic(1111) care(1106) }
{ analysi(2126) use(1163) compon(1037) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ method(1969) cluster(1462) data(1082) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ imag(2675) segment(2577) method(1081) }
{ 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) }
{ problem(2511) optim(1539) algorithm(950) }
{ chang(1828) time(1643) increas(1301) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ care(1570) inform(1187) nurs(1089) }
{ search(2224) databas(1162) retriev(909) }
{ case(1353) use(1143) diagnosi(1136) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ system(1050) medic(1026) inform(1018) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ blood(1257) pressur(1144) flow(957) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ sampl(1606) size(1419) use(1276) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }

Resumo

JECTIVE: The optimal allocation of organs in liver transplantation is a problem that can be resolved using machine-learning techniques. Classical methods of allocation included the assignment of an organ to the first patient on the waiting list without taking into account the characteristics of the donor and/or recipient. In this study, characteristics of the donor, recipient and transplant organ were used to determine graft survival. We utilised a dataset of liver transplants collected by eleven Spanish hospitals that provides data on the survival of patients three months after their operations.METHODS AND MATERIAL: To address the problem of organ allocation, the memetic Pareto evolutionary non-dominated sorting genetic algorithm 2 (MPENSGA2 algorithm), a multi-objective evolutionary algorithm, was used to train radial basis function neural networks, where accuracy was the measure used to evaluate model performance, along with the minimum sensitivity measurement. The neural network models obtained from the Pareto fronts were used to develop a rule-based system. This system will help medical experts allocate organs.RESULTS: The models obtained with the MPENSGA2 algorithm generally yielded competitive results for all performance metrics considered in this work, namely the correct classification rate (C), minimum sensitivity (MS), area under the receiver operating characteristic curve (AUC), root mean squared error (RMSE) and Cohen's kappa (Kappa). In general, the multi-objective evolutionary algorithm demonstrated a better performance than the mono-objective algorithm, especially with regard to the MS extreme of the Pareto front, which yielded the best values of MS (48.98) and AUC (0.5659). The rule-based system efficiently complements the current allocation system (model for end-stage liver disease, MELD) based on the principles of efficiency and equity. This complementary effect occurred in 55% of the cases used in the simulation. The proposed rule-based system minimises the prediction probability error produced by two sets of models (one of them formed by models guided by one of the objectives (entropy) and the other composed of models guided by the other objective (MS)), such that it maximises the probability of success in liver transplants, with success based on graft survival three months post-transplant.CONCLUSION: The proposed rule-based system is objective, because it does not involve medical experts (the expert's decision may be biased by several factors, such as his/her state of mind or familiarity with the patient). This system is a useful tool that aids medical experts in the allocation of organs; however, the final allocation decision must be made by an expert.

Resumo Limpo

jectiv optim alloc organ liver transplant problem can resolv use machinelearn techniqu classic method alloc includ assign organ first patient wait list without take account characterist donor andor recipi studi characterist donor recipi transplant organ use determin graft surviv utilis dataset liver transplant collect eleven spanish hospit provid data surviv patient three month operationsmethod materi address problem organ alloc memet pareto evolutionari nondomin sort genet algorithm mpensga algorithm multiobject evolutionari algorithm use train radial basi function neural network accuraci measur use evalu model perform along minimum sensit measur neural network model obtain pareto front use develop rulebas system system will help medic expert alloc organsresult model obtain mpensga algorithm general yield competit result perform metric consid work name correct classif rate c minimum sensit ms area receiv oper characterist curv auc root mean squar error rmse cohen kappa kappa general multiobject evolutionari algorithm demonstr better perform monoobject algorithm especi regard ms extrem pareto front yield best valu ms auc rulebas system effici complement current alloc system model endstag liver diseas meld base principl effici equiti complementari effect occur case use simul propos rulebas system minimis predict probabl error produc two set model one form model guid one object entropi compos model guid object ms maximis probabl success liver transplant success base graft surviv three month posttransplantconclus propos rulebas system object involv medic expert expert decis may bias sever factor hisher state mind familiar patient system use tool aid medic expert alloc organ howev final alloc decis must made expert

Resumos Similares

BMC Med Inform Decis Mak - Use of outcomes to evaluate surveillance systems for bioterrorist attacks. ( 0,685344126645581 )
Med Decis Making - Performance profiling in primary care: does the choice of statistical model matter? ( 0,666115533697765 )
BMC Med Inform Decis Mak - A three-step approach for the derivation and validation of high-performing predictive models using an operational dataset: congestive heart failure readmission case study. ( 0,665165123321051 )
Comput Math Methods Med - Variable selection in ROC regression. ( 0,661727760551931 )
Comput. Biol. Med. - A ternary model of decompression sickness in rats. ( 0,658752061575089 )
J Biomed Inform - Statistical process control for validating a classification tree model for predicting mortality--a novel approach towards temporal validation. ( 0,653676240147322 )
J Biomed Inform - Prediction of influenza vaccination outcome by neural networks and logistic regression. ( 0,649524544374677 )
Med Decis Making - A comparison of methods for converting DCE values onto the full health-dead QALY scale. ( 0,647665403716723 )
Med Decis Making - Contrasting two frameworks for ROC analysis of ordinal ratings. ( 0,647579673030231 )
Appl Clin Inform - Comparing predictions made by a prediction model, clinical score, and physicians: pediatric asthma exacerbations in the emergency department. ( 0,639522546553905 )
BMC Med Inform Decis Mak - Harmonisation of variables names prior to conducting statistical analyses with multiple datasets: an automated approach. ( 0,633914473177837 )
J Am Med Inform Assoc - An improved model for predicting postoperative nausea and vomiting in ambulatory surgery patients using physician-modifiable risk factors. ( 0,631759819748834 )
IEEE Trans Image Process - DEB: definite error bounded tangent estimator for digital curves. ( 0,628613724519898 )
Int J Health Geogr - Modeling larval malaria vector habitat locations using landscape features and cumulative precipitation measures. ( 0,621957890477413 )
J. Comput. Biol. - Prediction of siRNA potency using sparse logistic regression. ( 0,617029143317353 )
J Am Med Inform Assoc - A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data. ( 0,61429995154199 )
Med Decis Making - Methods for Performing Survival Curve Quality-of-Life Assessments. ( 0,612645559684116 )
Int J Comput Assist Radiol Surg - Controlling motion prediction errors in radiotherapy with relevance vector machines. ( 0,609730393421049 )
BMC Med Inform Decis Mak - Evaluation of prediction models for the staging of prostate cancer. ( 0,607881571746854 )
J Biomed Inform - Decision-making model for early diagnosis of congestive heart failure using rough set and decision tree approaches. ( 0,60782230609849 )
Comput. Biol. Med. - A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks. ( 0,60298842942257 )
J Chem Inf Model - Two new parameters based on distances in a receiver operating characteristic chart for the selection of classification models. ( 0,600581774283761 )
Med Decis Making - Lehmann family of ROC curves. ( 0,599205767783355 )
BMC Med Inform Decis Mak - Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model. ( 0,595495939233236 )
Brief. Bioinformatics - Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them). ( 0,595100322309239 )
Med Decis Making - Application of an artificial neural network to predict postinduction hypotension during general anesthesia. ( 0,593795279533024 )
J Med Syst - Effective automated prediction of vertebral column pathologies based on logistic model tree with SMOTE preprocessing. ( 0,591830798815447 )
Comput Biol Chem - Using ensemble methods to deal with imbalanced data in predicting protein-protein interactions. ( 0,591622826078762 )
J Med Syst - Classifying hospitals as mortality outliers: logistic versus hierarchical logistic models. ( 0,591236277314646 )
Lifetime Data Anal - Understanding increments in model performance metrics. ( 0,590492929748331 )
BMC Med Inform Decis Mak - Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population. ( 0,59000111224475 )
Comput Methods Programs Biomed - Single stage and multistage classification models for the prediction of liver fibrosis degree in patients with chronic hepatitis C infection. ( 0,588274289221317 )
J Am Med Inform Assoc - From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system. ( 0,585960582958539 )
J Biomed Inform - An empirical approach to model selection through validation for censored survival data. ( 0,585730966116876 )
J Chem Inf Model - Interpretable, probability-based confidence metric for continuous quantitative structure-activity relationship models. ( 0,58473344568619 )
J Clin Monit Comput - Effect of concurrent oxygen therapy on accuracy of forecasting imminent postoperative desaturation. ( 0,583350492335564 )
J Chem Inf Model - Using random forest to model the domain applicability of another random forest model. ( 0,580660766499074 )
IEEE Trans Image Process - Network-based H.264/AVC whole frame loss visibility model and frame dropping methods. ( 0,580239854584663 )
Comput Methods Programs Biomed - Development of a daily mortality probability prediction model from Intensive Care Unit patients using a discrete-time event history analysis. ( 0,578578204565832 )
Methods Inf Med - Limited sampling strategies to estimate the area under the concentration-time curve. Biases and a proposed more accurate method. ( 0,576889131105279 )
Spat Spatiotemporal Epidemiol - Assessment of land use factors associated with dengue cases in Malaysia using Boosted Regression Trees. ( 0,574657767768076 )
J Chem Inf Model - Capturing the crystal: prediction of enthalpy of sublimation, crystal lattice energy, and melting points of organic compounds. ( 0,573804319072277 )
BMC Med Inform Decis Mak - Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model. ( 0,57341445801314 )
Spat Spatiotemporal Epidemiol - Modeling habitat suitability for occurrence of highly pathogenic avian influenza virus H5N1 in domestic poultry in Asia: a spatial multicriteria decision analysis approach. ( 0,572673376281472 )
IEEE Trans Vis Comput Graph - Hierarchical and Controlled Advancement for Continuous Collision Detection of Rigid and Articulated Models. ( 0,570279514926558 )
Int J Health Geogr - Prediction of high-risk areas for visceral leishmaniasis using socioeconomic indicators and remote sensing data. ( 0,569088359611108 )
J Clin Monit Comput - Use of genetic programming, logistic regression, and artificial neural nets to predict readmission after coronary artery bypass surgery. ( 0,568263534503635 )
AMIA Annu Symp Proc - Predicting Surgical Risk: How Much Data is Enough? ( 0,568024122066687 )
IEEE Trans Image Process - Spatial sparsity-induced prediction (SIP) for images and video: a simple way to reject structured interference. ( 0,567199091452072 )
Med Decis Making - Adaptation of clinical prediction models for application in local settings. ( 0,565186123159722 )
J Biomed Inform - Partial least squares and logistic regression random-effects estimates for gene selection in supervised classification of gene expression data. ( 0,564942616883685 )
BMC Med Inform Decis Mak - A method for managing re-identification risk from small geographic areas in Canada. ( 0,563734493789866 )
IEEE Trans Neural Netw Learn Syst - Two Efficient Twin ELM Methods With Prediction Interval. ( 0,562756425254153 )
BMC Med Inform Decis Mak - Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups. ( 0,56221498656437 )
BMC Med Inform Decis Mak - Bayesian predictors of very poor health related quality of life and mortality in patients with COPD. ( 0,561927934425508 )
Int J Health Geogr - Assessing the effects of variables and background selection on the capture of the tick climate niche. ( 0,561838123059981 )
Artif Intell Med - Predicting the need for CT imaging in children with minor head injury using an ensemble of Naive Bayes classifiers. ( 0,561818993348252 )
Artif Intell Med - Operation room tool handling and miscommunication scenarios: an object-process methodology conceptual model. ( 0,560122741696796 )
Comput Methods Programs Biomed - A warning concerning the estimation of multinomial logistic models with correlated responses in SAS. ( 0,55913912527484 )
Int J Med Inform - Application of data mining to the identification of critical factors in patient falls using a web-based reporting system. ( 0,558873168010457 )
Artif Intell Med - Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers. ( 0,558680398257766 )
J Chem Inf Model - dREL: a relational expression language for dictionary methods. ( 0,558595859977967 )
Appl Clin Inform - Exploring the value of clinical data standards to predict hospitalization of home care patients. ( 0,55775094697772 )
Artif Intell Med - An evaluation of heuristics for rule ranking. ( 0,556627936373257 )
Med Decis Making - Evaluation of markers and risk prediction models: overview of relationships between NRI and decision-analytic measures. ( 0,556309468947718 )
Comput. Biol. Med. - A leave-one-out cross-validation SAS macro for the identification of markers associated with survival. ( 0,553236647627285 )
Comput Math Methods Med - Prediction of BP reactivity to talking using hybrid soft computing approaches. ( 0,552413754762777 )
BMC Med Inform Decis Mak - Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies. ( 0,551410998822348 )
Med Decis Making - Performance of a mathematical model to forecast lives saved from HIV treatment expansion in resource-limited settings. ( 0,55131816855369 )
Brief. Bioinformatics - Adjusting confounders in ranking biomarkers: a model-based ROC approach. ( 0,550436150199868 )
J Chem Inf Model - Ligand efficiency-based support vector regression models for predicting bioactivities of ligands to drug target proteins. ( 0,55035179318986 )
Artif Intell Med - Prediction of human major histocompatibility complex class II binding peptides by continuous kernel discrimination method. ( 0,549702999235841 )
J Biomed Inform - Towards probabilistic decision support in public health practice: predicting recent transmission of tuberculosis from patient attributes. ( 0,548996259975718 )
Med Decis Making - Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting: An Application of Machine Learning Methods. ( 0,548821866847891 )
J Chem Inf Model - Homology modeling of human muscarinic acetylcholine receptors. ( 0,546358393394003 )
J Integr Bioinform - Comparison of different algorithms for simultaneous estimation of multiple parameters in kinetic metabolic models. ( 0,545740435978996 )
IEEE J Biomed Health Inform - The effect of sample age and prediction resolution on myocardial infarction risk prediction. ( 0,545478871770886 )
Comput Math Methods Med - Modified logistic regression models using gene coexpression and clinical features to predict prostate cancer progression. ( 0,543212761755075 )
Neural Comput - Sample skewness as a statistical measurement of neuronal tuning sharpness. ( 0,542981298809247 )
J Med Syst - A new approach: role of data mining in prediction of survival of burn patients. ( 0,54082080638839 )
Methods Inf Med - An experimental evaluation of boosting methods for classification. ( 0,540508276295698 )
J Am Med Inform Assoc - Supervised embedding of textual predictors with applications in clinical diagnostics for pediatric cardiology. ( 0,539769299876633 )
Med Biol Eng Comput - Prediction of persistence of combined evidence-based cardiovascular medications in patients with acute coronary syndrome after hospital discharge using neural networks. ( 0,539644093590082 )
Methods Inf Med - Sensor-based fall risk assessment--an expert 'to go'. ( 0,539629453405073 )
AMIA Annu Symp Proc - Developing predictive models using electronic medical records: challenges and pitfalls. ( 0,53897216253385 )
Comput Methods Programs Biomed - Exploring an optimal vector autoregressive model for multi-channel pulmonary sound data. ( 0,538772389073818 )
Comput Methods Programs Biomed - PSHREG: a SAS macro for proportional and nonproportional subdistribution hazards regression. ( 0,538762937110464 )
J Chem Inf Model - Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosis. ( 0,538417815219861 )
Comput Methods Programs Biomed - Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods. ( 0,537569294831701 )
Artif Intell Med - Multilevel Bayesian networks for the analysis of hierarchical health care data. ( 0,5364371136013 )
Med Decis Making - Constructing proper ROCs from ordinal response data using weighted power functions. ( 0,536250432948546 )
Comput Methods Programs Biomed - Prediction of postprandial blood glucose under uncertainty and intra-patient variability in type 1 diabetes: a comparative study of three interval models. ( 0,535700389425478 )
AMIA Annu Symp Proc - Comparing predictive models of glioblastoma multiforme built using multi-institutional and local data sources. ( 0,534732291370668 )
Comput. Biol. Med. - Prediction of survival of ICU patients using computational intelligence. ( 0,534470746971413 )
Comput Methods Programs Biomed - Monitoring of anticoagulant therapy applying a dynamic statistical model. ( 0,534418890360922 )
AMIA Annu Symp Proc - Development and implementation of a real-time 30-day readmission predictive model. ( 0,533744058603165 )
Artif Intell Med - Improved modeling of clinical data with kernel methods. ( 0,532975184930063 )
Comput Math Methods Med - Iterative reweighted noninteger norm regularizing SVM for gene expression data classification. ( 0,531682957475115 )
Appl Clin Inform - Patient no-show predictive model development using multiple data sources for an effective overbooking approach. ( 0,527912369783142 )
IEEE J Biomed Health Inform - The technologically integrated oncosimulator: combining multiscale cancer modeling with information technology in the in silico oncology context. ( 0,525623589232688 )