Artif Intell Med - Computer-aided diagnosis of pulmonary nodules using a two-step approach for feature selection and classifier ensemble construction.

Tópicos

{ featur(3375) classif(2383) classifi(1994) }
{ design(1359) user(1324) use(1319) }
{ method(1969) cluster(1462) data(1082) }
{ error(1145) method(1030) estim(1020) }
{ search(2224) databas(1162) retriev(909) }
{ sampl(1606) size(1419) use(1276) }
{ first(2504) two(1366) second(1323) }
{ system(1976) rule(880) can(841) }
{ blood(1257) pressur(1144) flow(957) }
{ assess(1506) score(1403) qualiti(1306) }
{ data(2317) use(1299) case(1017) }
{ method(2212) result(1239) propos(1039) }
{ take(945) account(800) differ(722) }
{ treatment(1704) effect(941) patient(846) }
{ concept(1167) ontolog(924) domain(897) }
{ perform(1367) use(1326) method(1137) }
{ model(2656) set(1616) predict(1553) }
{ data(1737) use(1416) pattern(1282) }
{ motion(1329) object(1292) video(1091) }
{ model(3480) simul(1196) paramet(876) }
{ patient(2837) hospit(1953) medic(668) }
{ cost(1906) reduc(1198) effect(832) }
{ analysi(2126) use(1163) compon(1037) }
{ high(1669) rate(1365) level(1280) }
{ activ(1452) weight(1219) physic(1104) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ inform(2794) health(2639) internet(1427) }
{ imag(1057) registr(996) error(939) }
{ imag(2830) propos(1344) filter(1198) }
{ imag(2675) segment(2577) method(1081) }
{ studi(2440) review(1878) systemat(933) }
{ learn(2355) train(1041) set(1003) }
{ clinic(1479) use(1117) guidelin(835) }
{ method(1557) propos(1049) approach(1037) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ research(1085) discuss(1038) issu(1018) }
{ compound(1573) activ(1297) structur(1058) }
{ group(2977) signific(1463) compar(1072) }
{ gene(2352) biolog(1181) express(1162) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ structur(1116) can(940) graph(676) }
{ implement(1333) system(1263) develop(1122) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ can(774) often(719) complex(702) }
{ measur(2081) correl(1212) valu(896) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ network(2748) neural(1063) input(814) }
{ patient(2315) diseas(1263) diabet(1191) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ chang(1828) time(1643) increas(1301) }
{ 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) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ studi(1119) effect(1106) posit(819) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ data(3008) multipl(1320) sourc(1022) }
{ activ(1138) subject(705) human(624) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ health(1844) social(1437) communiti(874) }
{ 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) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

JECTIVE: Accurate classification methods are critical in computer-aided diagnosis (CADx) and other clinical decision support systems. Previous research has reported on methods for combining genetic algorithm (GA) feature selection with ensemble classifier systems in an effort to increase classification accuracy. In this study, we describe a CADx system for pulmonary nodules using a two-step supervised learning system combining a GA with the random subspace method (RSM), with the aim of exploring algorithm design parameters and demonstrating improved classification performance over either the GA or RSM-based ensembles alone.METHODS AND MATERIALS: We used a retrospective database of 125 pulmonary nodules (63 benign; 62 malignant) with CT volumes and clinical history. A total of 216 features were derived from the segmented image data and clinical history. Ensemble classifiers using RSM or GA-based feature selection were constructed and tested via leave-one-out validation with feature selection and classifier training executed within each iteration. We further tested a two-step approach using a GA ensemble to first assess the relevance of the features, and then using this information to control feature selection during a subsequent RSM step. The base classification was performed using linear discriminant analysis (LDA).RESULTS: The RSM classifier alone achieved a maximum leave-one-out Az of 0.866 (95% confidence interval: 0.794-0.919) at a subset size of s=36 features. The GA ensemble yielded an Az of 0.851 (0.775-0.907). The proposed two-step algorithm produced a maximum Az value of 0.889 (0.823-0.936) when the GA ensemble was used to completely remove less relevant features from the second RSM step, with similar results obtained when the GA-LDA results were used to reduce but not eliminate the occurrence of certain features. After accounting for correlations in the data, the leave-one-out Az in the two-step method was significantly higher than in the RSM and the GA-LDA.CONCLUSIONS: We have developed a CADx system for evaluation of pulmonary nodule based on a two-step feature selection and ensemble classifier algorithm. We have shown that by combining classifier ensemble algorithms in this two-step manner, it is possible to predict the malignancy for solitary pulmonary nodules with a performance exceeding that of either of the individual steps.

Resumo Limpo

jectiv accur classif method critic computeraid diagnosi cadx clinic decis support system previous research report method combin genet algorithm ga featur select ensembl classifi system effort increas classif accuraci studi describ cadx system pulmonari nodul use twostep supervis learn system combin ga random subspac method rsm aim explor algorithm design paramet demonstr improv classif perform either ga rsmbase ensembl alonemethod materi use retrospect databas pulmonari nodul benign malign ct volum clinic histori total featur deriv segment imag data clinic histori ensembl classifi use rsm gabas featur select construct test via leaveoneout valid featur select classifi train execut within iter test twostep approach use ga ensembl first assess relev featur use inform control featur select subsequ rsm step base classif perform use linear discrimin analysi ldaresult rsm classifi alon achiev maximum leaveoneout az confid interv subset size s featur ga ensembl yield az propos twostep algorithm produc maximum az valu ga ensembl use complet remov less relev featur second rsm step similar result obtain galda result use reduc elimin occurr certain featur account correl data leaveoneout az twostep method signific higher rsm galdaconclus develop cadx system evalu pulmonari nodul base twostep featur select ensembl classifi algorithm shown combin classifi ensembl algorithm twostep manner possibl predict malign solitari pulmonari nodul perform exceed either individu step

Resumos Similares

Comput. Biol. Med. - Contourlet-based mammography mass classification using the SVM family. ( 0,89063682841572 )
Int J Comput Assist Radiol Surg - Building an ensemble system for diagnosing masses in mammograms. ( 0,877882715917361 )
Comput. Biol. Med. - An ensemble system for automatic sleep stage classification using single channel EEG signal. ( 0,875014859187314 )
Comput. Biol. Med. - Pairwise FCM based feature weighting for improved classification of vertebral column disorders. ( 0,871912410729684 )
J Biomed Inform - Automatic figure classification in bioscience literature. ( 0,867358382218315 )
J Med Syst - A robust multi-class feature selection strategy based on Rotation Forest Ensemble algorithm for diagnosis of Erythemato-Squamous diseases. ( 0,865407945703502 )
Comput Math Methods Med - Comparison of different EHG feature selection methods for the detection of preterm labor. ( 0,863230090415391 )
Comput Methods Programs Biomed - A random forest classifier for lymph diseases. ( 0,862790373629059 )
Comput Math Methods Med - SVM versus MAP on accelerometer data to distinguish among locomotor activities executed at different speeds. ( 0,862416573476583 )
Int J Neural Syst - Single-trial motor imagery classification using asymmetry ratio, phase relation, wavelet-based fractal, and their selected combination. ( 0,862066036436287 )
J Biomed Inform - A fast gene selection method for multi-cancer classification using multiple support vector data description. ( 0,855563259790846 )
Comput Methods Programs Biomed - Automatic cervical cell segmentation and classification in Pap smears. ( 0,852480776965533 )
Comput Biol Chem - Information-theoretic approaches to SVM feature selection for metagenome read classification. ( 0,8513560432015 )
J Med Syst - SVM feature selection based rotation forest ensemble classifiers to improve computer-aided diagnosis of Parkinson disease. ( 0,850092690606894 )
Comput Methods Programs Biomed - A new hybrid intelligent system for accurate detection of Parkinson's disease. ( 0,847730120266022 )
J Med Syst - A comparative study on classification of sleep stage based on EEG signals using feature selection and classification algorithms. ( 0,843272014993902 )
Comput Biol Chem - A novel divide-and-merge classification for high dimensional datasets. ( 0,843002656497047 )
Comput Biol Chem - Derivation of an artificial gene to improve classification accuracy upon gene selection. ( 0,84260327630199 )
Comput. Biol. Med. - Fast and efficient lung disease classification using hierarchical one-against-all support vector machine and cost-sensitive feature selection. ( 0,839837543351102 )
Comput. Biol. Med. - A novel class dependent feature selection method for cancer biomarker discovery. ( 0,833325042606888 )
Artif Intell Med - An intelligent classifier for prognosis of cardiac resynchronization therapy based on speckle-tracking echocardiograms. ( 0,832820730271948 )
Comput Math Methods Med - Discrimination between Alzheimer's disease and mild cognitive impairment using SOM and PSO-SVM. ( 0,828299825881051 )
Comput Biol Chem - Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm. ( 0,828186597098343 )
Artif Intell Med - Texture feature ranking with relevance learning to classify interstitial lung disease patterns. ( 0,826100311726549 )
Comput. Biol. Med. - Disulfide connectivity prediction based on structural information without a prior knowledge of the bonding state of cysteines. ( 0,825333160045716 )
Int J Comput Assist Radiol Surg - Multimodality GPU-based computer-assisted diagnosis of breast cancer using ultrasound and digital mammography images. ( 0,824143826834329 )
Comput. Biol. Med. - SVM-based feature selection to optimize sensitivity-specificity balance applied to weaning. ( 0,823469868960158 )
Comput. Biol. Med. - Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders. ( 0,821867395899212 )
J Med Syst - Automated diagnosis of Alzheimer disease using the scale-invariant feature transforms in magnetic resonance images. ( 0,821769653723718 )
J Med Syst - Enhanced cancer recognition system based on random forests feature elimination algorithm. ( 0,820781801149823 )
Comput. Biol. Med. - A classification system based on a new wrapper feature selection algorithm for the diagnosis of primary and secondary polycythemia. ( 0,817078098290442 )
J Med Syst - A three-stage expert system based on support vector machines for thyroid disease diagnosis. ( 0,814987604639001 )
Comput. Biol. Med. - Heartbeat classification using disease-specific feature selection. ( 0,813752202502874 )
Comput Methods Programs Biomed - Hepatitis disease diagnosis using a novel hybrid method based on support vector machine and simulated annealing (SVM-SA). ( 0,811065289430059 )
Int J Neural Syst - Improved adaptive splitting and selection: the hybrid training method of a classifier based on a feature space partitioning. ( 0,807749734009992 )
J Med Syst - A new expert system for diagnosis of lung cancer: GDA-LS_SVM. ( 0,80732846211959 )
Comput Math Methods Med - An ensemble-of-classifiers based approach for early diagnosis of Alzheimer's disease: classification using structural features of brain images. ( 0,803850945406791 )
Comput. Biol. Med. - A new dataset evaluation method based on category overlap. ( 0,799406754723311 )
J Med Syst - An intelligent system for lung cancer diagnosis using a new genetic algorithm based feature selection method. ( 0,798804432339626 )
J Med Syst - Detection of carotid artery disease by using Learning Vector Quantization Neural Network. ( 0,796519943990822 )
Comput Methods Programs Biomed - Performance comparison of machine learning methods for prognosis of hormone receptor status in breast cancer tissue samples. ( 0,796189586758721 )
Comput Math Methods Med - Feature selection in classification of eye movements using electrooculography for activity recognition. ( 0,796158172440296 )
IEEE J Biomed Health Inform - Support vector machine classification based on correlation prototypes applied to bone age assessment. ( 0,794991665006778 )
Comput. Biol. Med. - A hybrid feature selection method for DNA microarray data. ( 0,794208229677669 )
Int J Neural Syst - Combination of heterogeneous EEG feature extraction methods and stacked sequential learning for sleep stage classification. ( 0,794189973625956 )
Comput Methods Programs Biomed - Functional activity maps based on significance measures and Independent Component Analysis. ( 0,790786652410781 )
J Am Med Inform Assoc - Influenza detection from emergency department reports using natural language processing and Bayesian network classifiers. ( 0,790700453189249 )
J Am Med Inform Assoc - A comparative analysis of methods for predicting clinical outcomes using high-dimensional genomic datasets. ( 0,788653464269437 )
Int J Neural Syst - Extraction of neural control commands using myoelectric pattern recognition: a novel application in adults with cerebral palsy. ( 0,78834979319728 )
Comput. Biol. Med. - Ant colony optimization-based feature selection method for surface electromyography signals classification. ( 0,78792491152539 )
Comput Methods Programs Biomed - Understanding symptomatology of atherosclerotic plaque by image-based tissue characterization. ( 0,781708320501115 )
J Am Med Inform Assoc - N-gram support vector machines for scalable procedure and diagnosis classification, with applications to clinical free text data from the intensive care unit. ( 0,781667533686307 )
Comput Math Methods Med - An expert system based on Fisher score and LS-SVM for cardiac arrhythmia diagnosis. ( 0,780238477323575 )
Artif Intell Med - Selective voting in convex-hull ensembles improves classification accuracy. ( 0,777315850947292 )
J Med Syst - Symptomatic vs. asymptomatic plaque classification in carotid ultrasound. ( 0,776827851074279 )
IEEE J Biomed Health Inform - Recognizing common CT imaging signs of lung diseases through a new feature selection method based on Fisher criterion and genetic optimization. ( 0,774721768388397 )
Artif Intell Med - Improving the accuracy of suicide attempter classification. ( 0,773746533631812 )
Comput. Biol. Med. - On the relevance of automatically selected single-voxel MRS and multimodal MRI and MRSI features for brain tumour differentiation. ( 0,771990732735504 )
IEEE Trans Image Process - A novel technique for subpixel image classification based on support vector machine. ( 0,769732412087572 )
Artif Intell Med - Subpopulation-specific confidence designation for more informative biomedical classification. ( 0,76735234018629 )
IEEE J Biomed Health Inform - Computer-aided diagnosis in hysteroscopic imaging. ( 0,767175891138768 )
J Chem Inf Model - Choosing feature selection and learning algorithms in QSAR. ( 0,767075854195782 )
Brief. Bioinformatics - Class-imbalanced classifiers for high-dimensional data. ( 0,765459940579233 )
J Med Syst - Statistical analysis of textural features for improved classification of oral histopathological images. ( 0,76459599876637 )
Brief. Bioinformatics - Ensemble learning algorithms for classification of mtDNA into haplogroups. ( 0,764424917686055 )
Comput Methods Programs Biomed - An improved method of early diagnosis of smoking-induced respiratory changes using machine learning algorithms. ( 0,763714965072695 )
BMC Med Inform Decis Mak - Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes. ( 0,761788370568939 )
J Biomed Inform - Boosting performance of gene mention tagging system by hybrid methods. ( 0,760823843809834 )
J Med Syst - Classification of normal and diseased liver shapes based on Spherical Harmonics coefficients. ( 0,760337387335364 )
J Biomed Inform - An efficient statistical feature selection approach for classification of gene expression data. ( 0,758464441536485 )
J Chem Inf Model - Classifier ensemble based on feature selection and diversity measures for predicting the affinity of A(2B) adenosine receptor antagonists. ( 0,758150542074843 )
Med Biol Eng Comput - Wavelet-based sparse functional linear model with applications to EEGs seizure detection and epilepsy diagnosis. ( 0,757109280060337 )
Artif Intell Med - Electrocardiogram analysis using a combination of statistical, geometric, and nonlinear heart rate variability features. ( 0,756409929154078 )
J Med Syst - An integrated index for the identification of diabetic retinopathy stages using texture parameters. ( 0,755509924402233 )
Int J Neural Syst - Assessment of feature selection and classification approaches to enhance information from overnight oximetry in the context of apnea diagnosis. ( 0,75540465289359 )
IEEE Trans Image Process - Walsh-Hadamard transform kernel-based feature vector for shot boundary detection. ( 0,754940420747391 )
Comput. Biol. Med. - Neurocognitive disorder detection based on feature vectors extracted from VBM analysis of structural MRI. ( 0,754589427742641 )
IEEE Trans Image Process - Efficient HIK SVM learning for image classification. ( 0,754157666977193 )
Int J Comput Assist Radiol Surg - Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection. ( 0,752748940469853 )
Comput Math Methods Med - Principal feature analysis: a multivariate feature selection method for fMRI data. ( 0,752601309110803 )
J Med Syst - Classification of speech dysfluencies using LPC based parameterization techniques. ( 0,752544519147664 )
Comput. Biol. Med. - A new feature extraction framework based on wavelets for breast cancer diagnosis. ( 0,749987515847937 )
Comput Math Methods Med - Determination of fetal state from cardiotocogram using LS-SVM with particle swarm optimization and binary decision tree. ( 0,7489615999121 )
Neural Comput - An Infomax algorithm can perform both familiarity discrimination and feature extraction in a single network. ( 0,748516657310054 )
Comput Biol Chem - Multi objective SNP selection using pareto optimality. ( 0,747514937944872 )
Comput Math Methods Med - Comparison of the data classification approaches to diagnose spinal cord injury. ( 0,747159624121103 )
J Biomed Inform - A biological continuum based approach for efficient clinical classification. ( 0,74490330697926 )
J Med Syst - Down syndrome diagnosis based on Gabor Wavelet Transform. ( 0,744134436429032 )
Comput. Biol. Med. - Gene expression microarray classification using PCA-BEL. ( 0,741401738058447 )
J Med Syst - Computer aided diagnosis system for breast cancer based on color Doppler flow imaging. ( 0,741073548747164 )
Comput. Biol. Med. - Ensemble selection for feature-based classification of diabetic maculopathy images. ( 0,739030014557846 )
Comput. Biol. Med. - Classification of diffusion tensor images for the early detection of Alzheimer's disease. ( 0,737575016066809 )
Comput Biol Chem - CE-PLoc: an ensemble classifier for predicting protein subcellular locations by fusing different modes of pseudo amino acid composition. ( 0,737281754003063 )
IEEE J Biomed Health Inform - Automatic detection of atrial fibrillation in cardiac vibration signals. ( 0,737196168682459 )
Artif Intell Med - Selection of effective features for ECG beat recognition based on nonlinear correlations. ( 0,737086982766461 )
IEEE Trans Image Process - Human detection in images via piecewise linear support vector machines. ( 0,73372907755238 )
Comput Math Methods Med - Feature selection for better identification of subtypes of Guillain-Barr? syndrome. ( 0,732813131237461 )
Comput Methods Programs Biomed - ECG beat classification using a cost sensitive classifier. ( 0,732668392915714 )
Int J Neural Syst - On the segmentation and classification of hand radiographs. ( 0,731729763281176 )
Med Biol Eng Comput - Feature selection on movement imagery discrimination and attention detection. ( 0,730707526985759 )