Search Results - carl AND random tree algorithm*

Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7 by Ramos-Gomez, Francisco, Marcus, Marvin, Maida, Carl A., Wang, Yan, Kinsler, Janni J., Xiong, Di, Lee, Steve Y., Hays, Ron D., Shen, Jie, Crall, James J., Liu, Honghu

“…–7 years of age living in Los Angeles County. Random forest (a machine learning algorithm…”
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Detection of Subtle ECG Changes Despite Superimposed Artifacts by Different Machine Learning Algorithms by Noitz, Matthias, Mörtl, Christoph, Böck, Carl, Mahringer, Christoph, Bodenhofer, Ulrich, Dünser, Martin W., Meier, Jens

“… In this theoretical, proof-of-concept study, we investigated the potential of five different machine learning algorithms [random forests (RFs…”
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The Application of Tree-Based Algorithms on Classifying Shunting Yard Departure Status by Minbashi, Niloofar, Bohlin, Markus, Palmqvist, Carl-William, Kordnejad, Behzad

“… In this paper, we compare the performance of tree-based methods (decision trees and random forests…”
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A Comparison of Machine Learning Algorithms and Feature Sets for Automatic Vocal Emotion Recognition in Speech by Doğdu, Cem, Kessler, Thomas, Schneider, Dana, Shadaydeh, Maha, Schweinberger, Stefan R.

“…), J48 Decision Tree (DT), Support Vector Machine with Sequential Minimal Optimization (SMO), Random Forest (RF…”
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Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces by Fergus, Paul, Selvaraj, Malarvizhi, Chalmers, Carl

“…Human visual inspection of Cardiotocography traces is used to monitor the foetus during labour and avoid neonatal mortality and morbidity. The problem,…”
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A machine learning algorithm for automatic tumour board recommendations in prostate cancer patients by Sondermann, Marcus, Glaser, Hannah, Rentsch, Anke, Boehm, Katharina, Herout, Roman, Hölscher, Tobias, Lohaus, Fabian, Funer, Fabian, Miederer, Matthias, Thomas, Christian, Mehralivand, Sherif

“… Three ML algorithms—Decision Tree, Random Forest and K‐Nearest Neighbours (KNN)—were trained to predict recommendations for PSMA…”
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Tree-Encoded Conditional Random Fields for Image Synthesis by Jog, Amod, Carass, Aaron, Pham, Dzung L, Prince, Jerry L

“… imaging data in order to make them more suitable as consistent inputs for processing. We frame the image synthesis problem as an inference problem on a 3-D continuous-valued conditional random field (CRF…”
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Supervised Machine Learning for Cell Classification in Microwave Flow Cytometers by Ehrett, Carl, Keagle, Matthew, Braun, Benjamin, Harikumar, Nitya, Osterberg, Jeffrey, Dahal, Neelima, Wang, Pingshan

“… ML models, including random forest, XGBoost, K-neighbors, decision tree, and support vector machine (SVM…”
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Classifying flow cytometry data using Bayesian analysis helps to distinguish ALS patients from healthy controls by Räuber, Saskia, Nelke, Christopher, Schroeter, Christina B., Barman, Sumanta, Pawlitzki, Marc, Ingwersen, Jens, Akgün, Katja, Günther, Rene, Garza, Alejandra P., Marggraf, Michaela, Dunay, Ildiko Rita, Schreiber, Stefanie, Vielhaber, Stefan, Ziemssen, Tjalf, Melzer, Nico, Ruck, Tobias, Meuth, Sven G., Herty, Michael

“… The algorithm creates a Bayesian network that is a HC tree when including raw, ungated mFC data of a randomly selected healthy control cohort (HC…”
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Evaluation of machine learning algorithms using OCT and OCT angiography for the diagnosis of multiple sclerosis by Lozano, María Pilar Rojas, Mesa, Pablo García, Gutiérrez, Nuria Díaz, Valverde, Juan José Gómez

“… We evaluated classification algorithms such as Support Vector Machines, k‐Nearest Neighbour, Decision Trees, Random Forest, Extra Trees Classifier and Gaussian NB using data extracted from Ganglion Cell Analysis (8 parameters…”
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Machine learning–based prediction of transfusion by Mitterecker, Andreas, Hofmann, Axel, Trentino, Kevin M., Lloyd, Adam, Leahy, Michael F., Schwarzbauer, Karin, Tschoellitsch, Thomas, Böck, Carl, Hochreiter, Sepp, Meier, Jens

“…–based prediction algorithms to predict transfusion, massive transfusion, and the number of transfusions in patients admitted to a hospital…”
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Performance of Observation-Based Prediction Algorithms for Very Short-Range, Probabilistic Clear-Sky Condition Forecasting by Hall, Timothy J., Mutchler, Carl N., Bloy, Greg J., Thessin, Rachel N., Gaffney, Stephanie K., Lareau, Jonathan J.

“… geographic regions within the continental United States. Three of the methods were based on predictive learning algorithms including neural network, random forest, and regression tree…”
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3D interactive coronary artery segmentation using random forests and Markov random field optimization by Jingjing Deng, Xianghua Xie, Alcock, Rob, Roobottom, Carl

“… in a multi-scale fashion, and are fed into a random forests classifier, which assigns each voxel with probability values…”
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Identification and validation of genetic variants predictive of gait in standardbred horses by McCoy, Annette M., Beeson, Samantha K., Rubin, Carl-Johan, Andersson, Leif, Caputo, Paul, Lykkjen, Sigrid, Moore, Alison, Piercy, Richard J., Mickelson, James R., McCue, Molly E.

“…Several horse breeds have been specifically selected for the ability to exhibit alternative patterns of locomotion, or gaits. A premature stop codon in the…”
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A machine learning approach to explore predictors of graft detachment following posterior lamellar keratoplasty: a nationwide registry study by Muijzer, M. B., Hoven, C. M. W., Frank, L. E., Vink, G., Wisse, R. P. L.

“… In this research, we used three machine learning methods; a regularized logistic regression (lasso), classification tree analysis…”
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Predictive Model for Assessing Student Mental Health Risk Based on Academic Data Using Machine Learning Algorithm by Cabusas, Jerald P., Daleon, Cherry Ann G., Maningo, Carl Phillip A., Bustillo, James Cloyd M., Balighot, Bernie S., Pojas, Patrick Jasson S.

“… Three classifiersDecision Tree, Random Forest, and Support Vector Classifier (SVC)-were evaluated using a structured machine learning pipeline…”
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Satellite Remote Sensing for Stand Age Estimation in Tree Plantations: A Case Study Using Landsat Images and Machine Learning Algorithms by Soliman, Rachelle, Escasio, John Carl, Santillan, Jojene R.

“… algorithms was explored for detecting and estimating the stand ages of Falcata plantations…”
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Fast state-space methods for inferring dendritic synaptic connectivity by Pakman, Ari, Huggins, Jonathan, Smith, Carl, Paninski, Liam

“…We present fast methods for filtering voltage measurements and performing optimal inference of the location and strength of synaptic connections in large dendritic trees…”
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Discriminating Industrial and Smallholder Oil Palm Plantations in Indonesia Using Sentinel-1 Textural Features by Bethuel, Carl, Pellen, Julien, Arvor, Damien, Corgne, Samuel, Colin, Elise, Gignoux, Jeremie

“… We used machine learning algorithms (Random Forest vs. eXtreme Gradient Boosting Tree) with textural features calculated by the Grey Level Co-occurrence Matrix…”
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Sequential Imputation of Missing Spatio-Temporal Precipitation Data Using Random Forests by Mital, Utkarsh, Dwivedi, Dipankar, Brown, James B., Faybishenko, Boris, Painter, Scott L., Steefel, Carl I.

“…Meteorological records, including precipitation, commonly have missing values. Accurate imputation of missing precipitation values is challenging, however,…”
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