J Biomed Inform - An empirical approach to model selection through validation for censored survival data.

Tópicos

{ model(2341) predict(2261) use(1141) }
{ featur(3375) classif(2383) classifi(1994) }
{ general(901) number(790) one(736) }
{ model(2656) set(1616) predict(1553) }
{ estim(2440) model(1874) function(577) }
{ system(1976) rule(880) can(841) }
{ problem(2511) optim(1539) algorithm(950) }
{ cost(1906) reduc(1198) effect(832) }
{ can(981) present(881) function(850) }
{ method(1557) propos(1049) approach(1037) }
{ sampl(1606) size(1419) use(1276) }
{ use(2086) technolog(871) perceiv(783) }
{ use(976) code(926) identifi(902) }
{ process(1125) use(805) approach(778) }
{ motion(1329) object(1292) video(1091) }
{ error(1145) method(1030) estim(1020) }
{ risk(3053) factor(974) diseas(938) }
{ blood(1257) pressur(1144) flow(957) }
{ state(1844) use(1261) util(961) }
{ data(2317) use(1299) case(1017) }
{ model(3404) distribut(989) bayesian(671) }
{ measur(2081) correl(1212) valu(896) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(1119) effect(1106) posit(819) }
{ high(1669) rate(1365) level(1280) }
{ decis(3086) make(1611) patient(1517) }
{ inform(2794) health(2639) internet(1427) }
{ studi(2440) review(1878) systemat(933) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ chang(1828) time(1643) increas(1301) }
{ control(1307) perform(991) simul(935) }
{ perform(999) metric(946) measur(919) }
{ perform(1367) use(1326) method(1137) }
{ record(1888) medic(1808) patient(1693) }
{ research(1218) medic(880) student(794) }
{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
{ activ(1452) weight(1219) physic(1104) }
{ method(2212) result(1239) propos(1039) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ take(945) account(800) differ(722) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ 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) }
{ design(1359) user(1324) use(1319) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ spatial(1525) area(1432) region(1030) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ patient(2837) hospit(1953) medic(668) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ 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(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Medical prognostic models can be designed to predict the future course or outcome of disease progression after diagnosis or treatment. The existing variable selection methods may be precluded by full model advocates when we build a prediction model owing to their estimation bias and selection bias in right-censored time-to-event data. If our objective is to optimize predictive performance by some criterion, we can often achieve a reduced model that has a little bias with low variance, but whose overall performance is enhanced. To accomplish this goal, we propose a new variable selection approach that combines Stepwise Tuning in the Maximum Concordance Index (STMC) with Forward Nested Subset Selection (FNSS) in two stages. In the first stage, the proposed variable selection is employed to identify the best subset of risk factors optimized with the concordance index using inner cross-validation for optimism correction in the outer loop of cross-validation, yielding potentially different final models for each of the folds. We then feed the intermediate results of the prior stage into another selection method in the second stage to resolve the overfitting problem and to select a final model from the variation of predictors in the selected models. Two case studies on relatively different sized survival data sets as well as a simulation study demonstrate that the proposed approach is able to select an improved and reduced average model under a sufficient sample and event size compared with other selection methods such as stepwise selection using the likelihood ratio test, Akaike Information Criterion (AIC), and lasso. Finally, we achieve better final models in each dataset than their full models by most measures. These results of the model selection models and the final models are assessed in a systematic scheme through validation for the independent performance.

Resumo Limpo

medic prognost model can design predict futur cours outcom diseas progress diagnosi treatment exist variabl select method may preclud full model advoc build predict model owe estim bias select bias rightcensor timetoev data object optim predict perform criterion can often achiev reduc model littl bias low varianc whose overal perform enhanc accomplish goal propos new variabl select approach combin stepwis tune maximum concord index stmc forward nest subset select fnss two stage first stage propos variabl select employ identifi best subset risk factor optim concord index use inner crossvalid optim correct outer loop crossvalid yield potenti differ final model fold feed intermedi result prior stage anoth select method second stage resolv overfit problem select final model variat predictor select model two case studi relat differ size surviv data set well simul studi demonstr propos approach abl select improv reduc averag model suffici sampl event size compar select method stepwis select use likelihood ratio test akaik inform criterion aic lasso final achiev better final model dataset full model measur result model select model final model assess systemat scheme valid independ perform

Resumos Similares

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. ( 0,764766437087267 )
Comput Math Methods Med - Iterative reweighted noninteger norm regularizing SVM for gene expression data classification. ( 0,76161304525003 )
Methods Inf Med - An experimental evaluation of boosting methods for classification. ( 0,749560184638411 )
Comput Biol Chem - Using ensemble methods to deal with imbalanced data in predicting protein-protein interactions. ( 0,747501896232399 )
J. Comput. Biol. - Prediction of siRNA potency using sparse logistic regression. ( 0,744824827924251 )
Neural Comput - An extension of the receiver operating characteristic curve and AUC-optimal classification. ( 0,743018418767935 )
AMIA Annu Symp Proc - Clinical risk prediction by exploring high-order feature correlations. ( 0,742171728561253 )
Comput Methods Programs Biomed - Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods. ( 0,740763507751993 )
Comput. Biol. Med. - Pre-operative prediction of surgical morbidity in children: comparison of five statistical models. ( 0,728303654252424 )
Comput Math Methods Med - Variable selection in ROC regression. ( 0,723999180211723 )
Int J Health Geogr - Prediction of high-risk areas for visceral leishmaniasis using socioeconomic indicators and remote sensing data. ( 0,717863638744943 )
Comput. Biol. Med. - A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks. ( 0,713005603419641 )
BMC Med Inform Decis Mak - Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes. ( 0,705156169271974 )
J Chem Inf Model - Two new parameters based on distances in a receiver operating characteristic chart for the selection of classification models. ( 0,70194897528637 )
BMC Med Inform Decis Mak - Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning. ( 0,696419044610824 )
Artif Intell Med - Predicting the need for CT imaging in children with minor head injury using an ensemble of Naive Bayes classifiers. ( 0,694041936869512 )
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. ( 0,693965474310898 )
Comput Methods Programs Biomed - Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines. ( 0,691073877881605 )
Med Decis Making - Application of an artificial neural network to predict postinduction hypotension during general anesthesia. ( 0,689365027886622 )
J Med Syst - A new approach: role of data mining in prediction of survival of burn patients. ( 0,689306073288 )
Med Biol Eng Comput - Mortality prediction of rats in acute hemorrhagic shock using machine learning techniques. ( 0,689236715232868 )
IEEE J Biomed Health Inform - Novel fractal feature-based multiclass glaucoma detection and progression prediction. ( 0,685600010790235 )
J Am Med Inform Assoc - Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy. ( 0,685592270017225 )
Med Decis Making - Performance of a mathematical model to forecast lives saved from HIV treatment expansion in resource-limited settings. ( 0,685176890950926 )
Med Decis Making - Adaptation of clinical prediction models for application in local settings. ( 0,683902782961712 )
J Am Med Inform Assoc - An improved model for predicting postoperative nausea and vomiting in ambulatory surgery patients using physician-modifiable risk factors. ( 0,683859707100501 )
BMC Med Inform Decis Mak - Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population. ( 0,682796756079446 )
Appl Clin Inform - Comparing predictions made by a prediction model, clinical score, and physicians: pediatric asthma exacerbations in the emergency department. ( 0,680755444306559 )
J Biomed Inform - Partial least squares and logistic regression random-effects estimates for gene selection in supervised classification of gene expression data. ( 0,678111815437852 )
AMIA Annu Symp Proc - Application of Bayesian logistic regression to mining biomedical data. ( 0,677690480701157 )
Comput Methods Programs Biomed - ThyroScreen system: high resolution ultrasound thyroid image characterization into benign and malignant classes using novel combination of texture and discrete wavelet transform. ( 0,676703779611626 )
Comput. Biol. Med. - A ternary model of decompression sickness in rats. ( 0,676260917563802 )
J Chem Inf Model - Ligand efficiency-based support vector regression models for predicting bioactivities of ligands to drug target proteins. ( 0,675536620834185 )
Lifetime Data Anal - Understanding increments in model performance metrics. ( 0,674025324865164 )
J Am Med Inform Assoc - A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data. ( 0,673974477712681 )
Comput Math Methods Med - Modified logistic regression models using gene coexpression and clinical features to predict prostate cancer progression. ( 0,67224596378795 )
J Med Syst - Diagnosing breast masses in digital mammography using feature selection and ensemble methods. ( 0,670070094259175 )
Comput Methods Programs Biomed - Exploring an optimal vector autoregressive model for multi-channel pulmonary sound data. ( 0,668835052307171 )
Methods Inf Med - Limited sampling strategies to estimate the area under the concentration-time curve. Biases and a proposed more accurate method. ( 0,668774392296096 )
Methods Inf Med - Classification of postural profiles among mouth-breathing children by learning vector quantization. ( 0,660922878645437 )
Comput Methods Programs Biomed - Single stage and multistage classification models for the prediction of liver fibrosis degree in patients with chronic hepatitis C infection. ( 0,659684915931708 )
Int J Med Inform - Application of data mining to the identification of critical factors in patient falls using a web-based reporting system. ( 0,658963399678711 )
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. ( 0,658395208117622 )
Comput Math Methods Med - SNP selection in genome-wide association studies via penalized support vector machine with MAX test. ( 0,657592004777584 )
Spat Spatiotemporal Epidemiol - Assessment of land use factors associated with dengue cases in Malaysia using Boosted Regression Trees. ( 0,656590618517339 )
Med Decis Making - A comparison of methods for converting DCE values onto the full health-dead QALY scale. ( 0,655187828121026 )
J Biomed Inform - Decision-making model for early diagnosis of congestive heart failure using rough set and decision tree approaches. ( 0,655071452492593 )
Med Decis Making - Lehmann family of ROC curves. ( 0,654477847045242 )
Comput. Biol. Med. - Breast-cancer identification using HMM-fuzzy approach. ( 0,654243980412276 )
Comput Methods Programs Biomed - Comparative evaluation of support vector machines for computer aided diagnosis of lung cancer in CT based on a multi-dimensional data set. ( 0,649082690196818 )
BMC Med Inform Decis Mak - Evaluation of prediction models for the staging of prostate cancer. ( 0,647273920014054 )
BMC Med Inform Decis Mak - Use of outcomes to evaluate surveillance systems for bioterrorist attacks. ( 0,647140287340094 )
IEEE J Biomed Health Inform - Prediction of periventricular leukomalacia occurrence in neonates after heart surgery. ( 0,643922830757117 )
Comput Math Methods Med - Prediction of BP reactivity to talking using hybrid soft computing approaches. ( 0,642915517973114 )
Comput Math Methods Med - An efficient diagnosis system for Parkinson's disease using kernel-based extreme learning machine with subtractive clustering features weighting approach. ( 0,642420507544594 )
J Med Syst - Effective automated prediction of vertebral column pathologies based on logistic model tree with SMOTE preprocessing. ( 0,641008199835443 )
Artif Intell Med - White box radial basis function classifiers with component selection for clinical prediction models. ( 0,640395237027436 )
BMC Med Inform Decis Mak - Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups. ( 0,638715334646038 )
J Med Syst - Classifying hospitals as mortality outliers: logistic versus hierarchical logistic models. ( 0,638355347539688 )
IEEE J Biomed Health Inform - The effect of sample age and prediction resolution on myocardial infarction risk prediction. ( 0,638068656724785 )
AMIA Annu Symp Proc - Decision path models for patient-specific modeling of patient outcomes. ( 0,637974354061158 )
IEEE J Biomed Health Inform - Classification of color images of dermatological ulcers. ( 0,63734233090618 )
J Clin Monit Comput - Use of genetic programming, logistic regression, and artificial neural nets to predict readmission after coronary artery bypass surgery. ( 0,634611506237326 )
Med Decis Making - Constructing proper ROCs from ordinal response data using weighted power functions. ( 0,63452246749995 )
J Chem Inf Model - Predictive toxicology modeling: protocols for exploring hERG classification and Tetrahymena pyriformis end point predictions. ( 0,634519606652493 )
J Biomed Inform - Statistical process control for validating a classification tree model for predicting mortality--a novel approach towards temporal validation. ( 0,633522093148656 )
Comput. Biol. Med. - Statistical model based 3D shape prediction of postoperative trunks for non-invasive scoliosis surgery planning. ( 0,6318155026587 )
Med Decis Making - Performance profiling in primary care: does the choice of statistical model matter? ( 0,630964275078642 )
J Med Syst - Comparison of artificial neural networks with logistic regression for detection of obesity. ( 0,629818473136847 )
Artif Intell Med - Selective voting in convex-hull ensembles improves classification accuracy. ( 0,629110801876985 )
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. ( 0,62788307394345 )
BMC Med Inform Decis Mak - Bayesian predictors of very poor health related quality of life and mortality in patients with COPD. ( 0,627517266375793 )
J Chem Inf Model - Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosis. ( 0,627254942909665 )
IEEE Trans Neural Netw Learn Syst - Retargeted Least Squares Regression Algorithm. ( 0,627089155358333 )
J Biomed Inform - Use of Medical Subject Headings (MeSH) in Portuguese for categorizing web-based healthcare content. ( 0,623166047751446 )
IEEE Trans Image Process - Efficient image classification via multiple rank regression. ( 0,621631728893185 )
AMIA Annu Symp Proc - Predicting Surgical Risk: How Much Data is Enough? ( 0,621275338275495 )
J Med Syst - An intelligent system for lung cancer diagnosis using a new genetic algorithm based feature selection method. ( 0,618860029242608 )
Med Decis Making - Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting: An Application of Machine Learning Methods. ( 0,618608432742999 )
J Biomed Inform - Not just data: a method for improving prediction with knowledge. ( 0,616693905776397 )
Med Biol Eng Comput - New feature extraction approach for epileptic EEG signal detection using time-frequency distributions. ( 0,61450420399321 )
J Am Med Inform Assoc - Automated identification of extreme-risk events in clinical incident reports. ( 0,614403999462301 )
J Biomed Inform - Data mining methods for classification of Medium-Chain Acyl-CoA dehydrogenase deficiency (MCADD) using non-derivatized tandem MS neonatal screening data. ( 0,612604100462247 )
Comput. Biol. Med. - A leave-one-out cross-validation SAS macro for the identification of markers associated with survival. ( 0,61257256281932 )
BMC Med Inform Decis Mak - A novel differential diagnostic model based on multiple biological parameters for immunoglobulin A nephropathy. ( 0,611359845455269 )
Int J Health Geogr - Assessing the effects of variables and background selection on the capture of the tick climate niche. ( 0,609114066895792 )
Int J Health Geogr - Application of satellite precipitation data to analyse and model arbovirus activity in the tropics. ( 0,608466379904439 )
Artif Intell Med - Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers. ( 0,604724069426514 )
BMC Med Inform Decis Mak - Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model. ( 0,60468950950914 )
BMC Med Inform Decis Mak - Diabetic retinopathy risk prediction for fundus examination using sparse learning: a cross-sectional study. ( 0,60057606666647 )
Appl Clin Inform - Exploring the value of clinical data standards to predict hospitalization of home care patients. ( 0,598227964633408 )
BMC Med Inform Decis Mak - Predicting disease risks from highly imbalanced data using random forest. ( 0,597914127757945 )
BMC Med Inform Decis Mak - Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection. ( 0,597078895559958 )
IEEE Trans Image Process - Network-based H.264/AVC whole frame loss visibility model and frame dropping methods. ( 0,594439851899747 )
Med Decis Making - Contrasting two frameworks for ROC analysis of ordinal ratings. ( 0,594240984041717 )
BMC Med Inform Decis Mak - Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies. ( 0,592050101165691 )
Artif Intell Med - Comparative analysis of a-priori and a-posteriori dietary patterns using state-of-the-art classification algorithms: a case/case-control study. ( 0,591607474473321 )
IEEE J Biomed Health Inform - Computer-aided staging of lymphoma patients with FDG PET/CT imaging based on textural information. ( 0,591259777825878 )
BMC Med Inform Decis Mak - Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model. ( 0,590338495946627 )
J Med Syst - An integrated index for the identification of diabetic retinopathy stages using texture parameters. ( 0,588687219369719 )