Artif Intell Med - Supervised machine learning-based classification of oral malodor based on the microbiota in saliva samples.

Tópicos

{ featur(3375) classif(2383) classifi(1994) }
{ signal(2180) analysi(812) frequenc(800) }
{ model(2341) predict(2261) use(1141) }
{ learn(2355) train(1041) set(1003) }
{ compound(1573) activ(1297) structur(1058) }
{ error(1145) method(1030) estim(1020) }
{ clinic(1479) use(1117) guidelin(835) }
{ network(2748) neural(1063) input(814) }
{ high(1669) rate(1365) level(1280) }
{ decis(3086) make(1611) patient(1517) }
{ sequenc(1873) structur(1644) protein(1328) }
{ risk(3053) factor(974) diseas(938) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ method(1219) similar(1157) match(930) }
{ assess(1506) score(1403) qualiti(1306) }
{ concept(1167) ontolog(924) domain(897) }
{ general(901) number(790) one(736) }
{ howev(809) still(633) remain(590) }
{ perform(1367) use(1326) method(1137) }
{ record(1888) medic(1808) patient(1693) }
{ state(1844) use(1261) util(961) }
{ patient(1821) servic(1111) care(1106) }
{ detect(2391) sensit(1101) algorithm(908) }
{ can(774) often(719) complex(702) }
{ bind(1733) structur(1185) ligand(1036) }
{ patient(2315) diseas(1263) diabet(1191) }
{ framework(1458) process(801) describ(734) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ model(2220) cell(1177) simul(1124) }
{ model(3480) simul(1196) paramet(876) }
{ patient(2837) hospit(1953) medic(668) }
{ first(2504) two(1366) second(1323) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ imag(2830) propos(1344) filter(1198) }
{ imag(2675) segment(2577) method(1081) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ problem(2511) optim(1539) algorithm(950) }
{ chang(1828) time(1643) increas(1301) }
{ algorithm(1844) comput(1787) effici(935) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ 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) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ visual(1396) interact(850) tool(830) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ health(3367) inform(1360) care(1135) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }

Resumo

JECTIVE: This study presents an effective method of classifying oral malodor from oral microbiota in saliva by using a support vector machine (SVM), an artificial neural network (ANN), and a decision tree. This approach uses concentrations of methyl mercaptan in mouth air as an indicator of oral malodor, and peak areas of terminal restriction fragment (T-RF) length polymorphisms (T-RFLPs) of the 16S rRNA gene as data for supervised machine-learning methods, without identifying specific species producing oral malodorous compounds.METHODS: 16S rRNA genes were amplified from saliva samples from 309 subjects, and T-RFLP analysis was carried out with the DNA fragments. T-RFLP analysis provides information on microbiota consisting of fragment lengths and peak areas corresponding to bacterial strains. The peak area is equivalent to the frequency of a specific fragment when one molecule is selected from terminal fragments. Another frequency is obtained by dividing the number of species-containing samples by the total number of samples. An SVM, an ANN, and a decision tree were trained based on these two frequencies in 308 samples and classified the presence or absence of methyl mercaptan in mouth air from the remaining subject.RESULTS: The proportion that trained SVM expressed as entropy achieved the highest classification accuracy, with a sensitivity of 51.1% and specificity of 95.0%. The ANN and decision tree provided lower classification accuracies, and only classification by the ANN was improved by weighting with entropy from the frequency of appearance in samples, which increased the accuracy to 81.9% with a sensitivity of 60.2% and a specificity of 90.5%. The decision tree showed low classification accuracy under all conditions.CONCLUSIONS: Using T-RF proportions and frequencies, models to classify the presence of methyl mercaptan, a volatile sulfur-containing compound that causes oral malodor, were developed. SVM classifiers successfully classified the presence of methyl mercaptan with high specificity, and this classification is expected to be useful for screening saliva for oral malodor before visits to specialist clinics. Classification by a SVM and an ANN does not require the identification of the oral microbiota species responsible for the malodor, and the ANN also does not require the proportions of T-RFs.

Resumo Limpo

jectiv studi present effect method classifi oral malodor oral microbiota saliva use support vector machin svm artifici neural network ann decis tree approach use concentr methyl mercaptan mouth air indic oral malodor peak area termin restrict fragment trf length polymorph trflps s rrna gene data supervis machinelearn method without identifi specif speci produc oral malodor compoundsmethod s rrna gene amplifi saliva sampl subject trflp analysi carri dna fragment trflp analysi provid inform microbiota consist fragment length peak area correspond bacteri strain peak area equival frequenc specif fragment one molecul select termin fragment anoth frequenc obtain divid number speciescontain sampl total number sampl svm ann decis tree train base two frequenc sampl classifi presenc absenc methyl mercaptan mouth air remain subjectresult proport train svm express entropi achiev highest classif accuraci sensit specif ann decis tree provid lower classif accuraci classif ann improv weight entropi frequenc appear sampl increas accuraci sensit specif decis tree show low classif accuraci conditionsconclus use trf proport frequenc model classifi presenc methyl mercaptan volatil sulfurcontain compound caus oral malodor develop svm classifi success classifi presenc methyl mercaptan high specif classif expect use screen saliva oral malodor visit specialist clinic classif svm ann requir identif oral microbiota speci respons malodor ann also requir proport trfs

Resumos Similares

Med Biol Eng Comput - Wavelet-based sparse functional linear model with applications to EEGs seizure detection and epilepsy diagnosis. ( 0,784284233634802 )
Comput Methods Programs Biomed - Classification of the electrocardiogram signals using supervised classifiers and efficient features. ( 0,782786560688651 )
Int J Neural Syst - Application of quantum-behaved particle swarm optimization to motor imagery EEG classification. ( 0,774442009627581 )
Comput Math Methods Med - Knee joint vibration signal analysis with matching pursuit decomposition and dynamic weighted classifier fusion. ( 0,765847410209592 )
J Med Syst - Effect of multiscale PCA de-noising on EMG signal classification for diagnosis of neuromuscular disorders. ( 0,765025548118715 )
J Med Syst - Detection of carotid artery disease by using Learning Vector Quantization Neural Network. ( 0,764511319145213 )
Int J Neural Syst - Automated diagnosis of epilepsy using CWT, HOS and texture parameters. ( 0,758436139005216 )
Comput Methods Programs Biomed - Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients. ( 0,757997363510587 )
Int J Neural Syst - Comparison of ictal and interictal EEG signals using fractal features. ( 0,751420143455251 )
Comput. Biol. Med. - Medical decision support system for diagnosis of neuromuscular disorders using DWT and fuzzy support vector machines. ( 0,748198252049683 )
J Clin Monit Comput - Classification of sleep apnea types using wavelet packet analysis of short-term ECG signals. ( 0,745046696845537 )
Comput. Biol. Med. - Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders. ( 0,743116717046157 )
IEEE J Biomed Health Inform - Novel fractal feature-based multiclass glaucoma detection and progression prediction. ( 0,738807390011033 )
Comput Methods Programs Biomed - Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals. ( 0,735944040826913 )
Comput. Biol. Med. - Ant colony optimization-based feature selection method for surface electromyography signals classification. ( 0,733493464323299 )
J Clin Monit Comput - Identification of apnea during respiratory monitoring using support vector machine classifier: a pilot study. ( 0,731221108243382 )
Med Biol Eng Comput - Predicting termination of paroxysmal atrial fibrillation using empirical mode decomposition of the atrial activity and statistical features of the heart rate variability. ( 0,730603051996833 )
IEEE J Biomed Health Inform - Automatic detection of atrial fibrillation in cardiac vibration signals. ( 0,729861212967578 )
Comput Biol Chem - Information-theoretic approaches to SVM feature selection for metagenome read classification. ( 0,726550006258508 )
Artif Intell Med - Kernel machines for epilepsy diagnosis via EEG signal classification: a comparative study. ( 0,726547691000289 )
Artif Intell Med - Electrocardiogram analysis using a combination of statistical, geometric, and nonlinear heart rate variability features. ( 0,721045188155906 )
J Chem Inf Model - Classifying molecules using a sparse probabilistic kernel binary classifier. ( 0,719020505134857 )
Comput Biol Chem - CE-PLoc: an ensemble classifier for predicting protein subcellular locations by fusing different modes of pseudo amino acid composition. ( 0,713623473984707 )
Med Biol Eng Comput - SEMG-based hand motion recognition using cumulative residual entropy and extreme learning machine. ( 0,71287239523234 )
J Am Med Inform Assoc - Influenza detection from emergency department reports using natural language processing and Bayesian network classifiers. ( 0,712508169469447 )
J Med Syst - A comparative study on classification of sleep stage based on EEG signals using feature selection and classification algorithms. ( 0,711956528300732 )
J Chem Inf Model - A binary ant colony optimization classifier for molecular activities. ( 0,710700901036057 )
Med Biol Eng Comput - Application of recurrence quantification analysis to automatically estimate infant sleep states using a single channel of respiratory data. ( 0,710301934632597 )
Comput Methods Programs Biomed - Clustering technique-based least square support vector machine for EEG signal classification. ( 0,710152944956156 )
Comput. Biol. Med. - Feature extraction and recognition of ictal EEG using EMD and SVM. ( 0,710128286439683 )
Int J Neural Syst - Single-trial motor imagery classification using asymmetry ratio, phase relation, wavelet-based fractal, and their selected combination. ( 0,709224369108943 )
Comput Methods Programs Biomed - ECG beat classification using a cost sensitive classifier. ( 0,706842500183024 )
Med Biol Eng Comput - Classification of multichannel EEG patterns using parallel hidden Markov models. ( 0,70567305914634 )
J Am Med Inform Assoc - A comparative analysis of methods for predicting clinical outcomes using high-dimensional genomic datasets. ( 0,70378632329386 )
BMC Med Inform Decis Mak - Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes. ( 0,703547511468095 )
Comput Biol Chem - A novel divide-and-merge classification for high dimensional datasets. ( 0,703505309104181 )
Int J Neural Syst - Combination of heterogeneous EEG feature extraction methods and stacked sequential learning for sleep stage classification. ( 0,703292736531461 )
Int J Neural Syst - Extraction of neural control commands using myoelectric pattern recognition: a novel application in adults with cerebral palsy. ( 0,703211416392582 )
J Med Syst - Applying cybernetic technology to diagnose human pulmonary sounds. ( 0,702900901611303 )
Comput. Biol. Med. - Noninvasive detection of mechanical prosthetic heart valve disorder. ( 0,700663103200317 )
Comput. Biol. Med. - Contourlet-based mammography mass classification using the SVM family. ( 0,700447324316247 )
Comput. Biol. Med. - An ensemble system for automatic sleep stage classification using single channel EEG signal. ( 0,700334435022139 )
Artif Intell Med - Development of electroencephalographic pattern classifiers for real and imaginary thumb and index finger movements of one hand. ( 0,697840351989281 )
Comput Math Methods Med - Multivoxel pattern analysis for FMRI data: a review. ( 0,696540509667236 )
J Med Syst - Application of higher order spectra to identify epileptic EEG. ( 0,69633741245788 )
Brief. Bioinformatics - Class-imbalanced classifiers for high-dimensional data. ( 0,695858083482463 )
J Med Syst - Automatic and adaptive classification of electroencephalographic signals for brain computer interfaces. ( 0,694082108005065 )
J Integr Bioinform - On the parameter optimization of Support Vector Machines for binary classification. ( 0,69406600547596 )
J Med Syst - Symptomatic vs. asymptomatic plaque classification in carotid ultrasound. ( 0,693974644038337 )
J Med Syst - An integrated index for the identification of diabetic retinopathy stages using texture parameters. ( 0,693302751613892 )
IEEE J Biomed Health Inform - Extracting and Selecting Distinctive EEG Features for Efficient Epileptic Seizure Prediction. ( 0,691886579132075 )
Comput Biol Chem - Derivation of an artificial gene to improve classification accuracy upon gene selection. ( 0,691706550624934 )
J Med Syst - Automated screening of arrhythmia using wavelet based machine learning techniques. ( 0,69143490986572 )
Comput Methods Programs Biomed - Classification of normal and epileptic seizure EEG signals using wavelet transform, phase-space reconstruction, and Euclidean distance. ( 0,691428826920534 )
J Med Syst - A biomedical system based on artificial neural network and principal component analysis for diagnosis of the heart valve diseases. ( 0,689650100527414 )
Methods Inf Med - An experimental evaluation of boosting methods for classification. ( 0,689272486509375 )
Comput. Biol. Med. - Detection of seizures in EEG using subband nonlinear parameters and genetic algorithm. ( 0,688685924849658 )
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. ( 0,688508005770418 )
Comput Methods Programs Biomed - Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal. ( 0,688191177364403 )
J Med Syst - Detection and localization of myocardial infarction using K-nearest neighbor classifier. ( 0,687423316074832 )
Artif Intell Med - Selective voting in convex-hull ensembles improves classification accuracy. ( 0,687301269511868 )
Med Biol Eng Comput - Feature selection on movement imagery discrimination and attention detection. ( 0,687285412305079 )
J Med Syst - An intelligent system for lung cancer diagnosis using a new genetic algorithm based feature selection method. ( 0,685348769904844 )
Artif Intell Med - Improving the accuracy of suicide attempter classification. ( 0,684532926763173 )
Comput Methods Programs Biomed - A new hybrid intelligent system for accurate detection of Parkinson's disease. ( 0,68385944980079 )
Med Biol Eng Comput - Evaluation of feature extraction methods for EEG-based brain-computer interfaces in terms of robustness to slight changes in electrode locations. ( 0,681316422699377 )
J Med Syst - SVM feature selection based rotation forest ensemble classifiers to improve computer-aided diagnosis of Parkinson disease. ( 0,680215702795606 )
Comput. Biol. Med. - In silico prediction of spleen tyrosine kinase inhibitors using machine learning approaches and an optimized molecular descriptor subset generated by recursive feature elimination method. ( 0,679853253865293 )
Comput Methods Programs Biomed - An improved method of early diagnosis of smoking-induced respiratory changes using machine learning algorithms. ( 0,679622466679219 )
J Med Syst - Classification of normal and diseased liver shapes based on Spherical Harmonics coefficients. ( 0,678391652107206 )
J Med Syst - Usage of case-based reasoning, neural network and adaptive neuro-fuzzy inference system classification techniques in breast cancer dataset classification diagnosis. ( 0,677780100881019 )
Comput Math Methods Med - SVM versus MAP on accelerometer data to distinguish among locomotor activities executed at different speeds. ( 0,676609493868897 )
Comput Methods Programs Biomed - Automatic classification of sleep stages based on the time-frequency image of EEG signals. ( 0,676156937851248 )
Int J Comput Assist Radiol Surg - Building an ensemble system for diagnosing masses in mammograms. ( 0,675499140238307 )
Comput Methods Programs Biomed - Prediction of paroxysmal atrial fibrillation based on non-linear analysis and spectrum and bispectrum features of the heart rate variability signal. ( 0,673355870442686 )
Comput. Biol. Med. - Automatic classification of infant sleep based on instantaneous frequencies in a single-channel EEG signal. ( 0,673317200619958 )
J Med Syst - A robust multi-class feature selection strategy based on Rotation Forest Ensemble algorithm for diagnosis of Erythemato-Squamous diseases. ( 0,672423022631397 )
Comput. Biol. Med. - A novel class dependent feature selection method for cancer biomarker discovery. ( 0,672362886303026 )
Comput Methods Programs Biomed - A random forest classifier for lymph diseases. ( 0,670797462239967 )
Comput. Biol. Med. - Odorant recognition using biological responses recorded in olfactory bulb of rats. ( 0,670421792469592 )
IEEE Trans Image Process - A novel technique for subpixel image classification based on support vector machine. ( 0,669996302257979 )
BMC Med Inform Decis Mak - Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning. ( 0,669146141607268 )
Comput Methods Programs Biomed - Supervised hybrid feature selection based on PSO and rough sets for medical diagnosis. ( 0,66712347946712 )
AMIA Annu Symp Proc - Automatic Prediction of Conversion from Mild Cognitive Impairment to Probable Alzheimer's Disease using Structural Magnetic Resonance Imaging. ( 0,666068664819834 )
Med Biol Eng Comput - Signal feature extraction by multi-scale PCA and its application to respiratory sound classification. ( 0,66421385010186 )
Artif Intell Med - Computer-aided diagnosis of pulmonary nodules using a two-step approach for feature selection and classifier ensemble construction. ( 0,663287944073558 )
Comput. Biol. Med. - Decision forest for classification of gene expression data. ( 0,663232421733694 )
Comput. Biol. Med. - Heartbeat classification using disease-specific feature selection. ( 0,663054606086009 )
Med Biol Eng Comput - Automated detection of perinatal hypoxia using time-frequency-based heart rate variability features. ( 0,662918127606044 )
Comput Math Methods Med - Recursive feature selection with significant variables of support vectors. ( 0,662676671864804 )
J Biomed Inform - Automatic figure classification in bioscience literature. ( 0,661119031560771 )
Comput. Biol. Med. - Neurocognitive disorder detection based on feature vectors extracted from VBM analysis of structural MRI. ( 0,661110866747013 )
Med Biol Eng Comput - Efficient automatic classifiers for the detection of A phases of the cyclic alternating pattern in sleep. ( 0,660553174311806 )
J Clin Monit Comput - Heart rate variability analysis during central hypovolemia using wavelet transformation. ( 0,66014832081665 )
Comput Methods Programs Biomed - Complex extreme learning machine applications in terahertz pulsed signals feature sets. ( 0,659171057837707 )
Comput. Biol. Med. - Disulfide connectivity prediction based on structural information without a prior knowledge of the bonding state of cysteines. ( 0,659095268318405 )
Med Biol Eng Comput - Decision support system for age-related macular degeneration using discrete wavelet transform. ( 0,657360843525976 )
Comput. Biol. Med. - A statistical based feature extraction method for breast cancer diagnosis in digital mammogram using multiresolution representation. ( 0,657238205815948 )
IEEE Trans Image Process - Efficient HIK SVM learning for image classification. ( 0,657136965801335 )
J Med Syst - A new approach: role of data mining in prediction of survival of burn patients. ( 0,656205867459086 )