MissForest—non-parametric missing value imputation for mixed-type data

Cited by (1,024)

Items 201–300 of 1,024

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2. Missing value estimation using clustering and deep learning within multiple imputation framework
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3. Swiss national community survey on functioning after spinal cord injury: Protocol, characteristics of participants and determinants of non-response
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4. Customer profitability forecasting using Big Data analytics: A case study of the insurance industry
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5. Tree‐Based Models for Political Science Data
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6. Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: A comparison of machine learning approaches.
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7. Missing Data Imputation on IoT Sensor Networks: Implications for on-Site Sensor Calibration
   Nwamaka U. Okafor, Declan T. Delaney · 2021 · IEEE Sensors Journal
8. Relation Between Sex, Menopause, and White Matter Hyperintensities
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   Luciana V. Gatti, Camilla L. Cunha, Luciano Marani, Henrique Cassol, Cassiano Gustavo Messias, Egídio Arai, Scott Denning, Luciana S. Soler, Claudio Aparecido Almeida, ALBERTO W. SETZER et al. · 2023 · Nature
10. Phylogenetic correlates of extinction risk in mammals: species in older lineages are not at greater risk
    Luis D. Verde Arregoitia, Simon P. Blomberg, Diana O. Fisher · 2013 · Proceedings of the Royal Society B Biological Sciences
11. Assessing Predictive Properties of Genome-Wide Selection in Soybeans
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12. Multiple imputation by chained equations in praxis: Guidelines and review
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13. The Complex Interplay of Pain, Depression, and Anxiety Symptoms in Patients With Chronic Pain
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15. The effect of peri‐operative dexmedetomidine on the incidence of postoperative delirium in cardiac and non‐cardiac surgical patients: a randomised, double‐blind placebo‐controlled trial
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16. FIGAN: A Missing Industrial Data Imputation Method Customized for Soft Sensor Application
    Zoujing Yao, Chunhui Zhao · 2021 · IEEE Transactions on Automation Science and Engineering
17. Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population
    Alencar Xavier, Diego Jarquín, Réka Howard, Vishnu Ramasubramanian, James E. Specht, George Lewis Graef, William Dale Beavis, Brian W. Diers, Qijian Song, Perry B. Cregan et al. · 2017 · G3 Genes Genomes Genetics
18. Integrating machine learning techniques and physiology based heart rate features for antepartum fetal monitoring
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19. Development and Internal Validation of Machine Learning Algorithms for Preoperative Survival Prediction of Extremity Metastatic Disease
    Quirina C. B. S. Thio, Aditya V. Karhade, Paul T. Ogink, Jos A. M. Bramer, Marco L. Ferrone, Santiago A. Lozano Calderón, Kevin A. Raskin, Joseph Hasbrouck Schwab · 2019 · Clinical Orthopaedics and Related Research
20. Frailty Status Modifies the Efficacy of Exercise Training Among Patients With Chronic Heart Failure and Reduced Ejection Fraction: An Analysis From the HF-ACTION Trial
    Ambarish Pandey, Matthew W. Segar, Sumitabh Singh, Gordon R. Reeves, Christopher J. O’Connor, Ileana L. Piña, David J. Whellan, William E. Kraus, Robert John Mentz, Dalane W. Kitzman · 2022 · Circulation
21. Cross-validation based K nearest neighbor imputation for software quality datasets: An empirical study
    Jianglin Huang, Jacky Keung, Federica Sarro, Yan‐Fu Li, Y.T. Yu, W. K. Chan, Hongyi Sun · 2017 · Journal of Systems and Software
22. Personalized treatment selection in routine care: Integrating machine learning and statistical algorithms to recommend cognitive behavioral or psychodynamic therapy
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23. TidyMass an object-oriented reproducible analysis framework for LC–MS data
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24. Prediction of Photochemical Properties of Dissolved Organic Matter Using Machine Learning
    Zhiyang Liao, Jinrong Lu, Kunting Xie, Yi Wang, Yong Yuan · 2023 · Environmental Science & Technology
25. A review on missing values for main challenges and methods
    Lijuan Ren, Tao Wang, Aïcha Sekhari, Haiqing Zhang, Abdelaziz Bouras · 2023 · Information Systems
26. PalmTraits 1.0, a species-level functional trait database of palms worldwide
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27. Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms
    Florian Lamping, Thomas Jack, Nicole Rübsamen, Michael Sasse, Philipp Beerbaum, Rafael Mikolajczyk, Martin Boehne, André Karch · 2018 · BMC Pediatrics
28. High-throughput proteomic profiling of the fish liver following bacterial infection
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29. The metaRbolomics Toolbox in Bioconductor and beyond
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30. Multiple imputation using nearest neighbor methods
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31. Digital biomarkers of anxiety disorder symptom changes: Personalized deep learning models using smartphone sensors accurately predict anxiety symptoms from ecological momentary assessments
    Jacobson, Nicholas C., Bhattacharya, Sukanya · 2022 · Behaviour Research and Therapy
32. Serum or Plasma (and Which Plasma), That Is the Question
    Alessia Vignoli, Leonardo Tenori, Cristina Morsiani, Paola Turano, Miriam Capri, Claudio Luchinat · 2022 · Journal of Proteome Research
33. Dealing with missing values in proteomics data
    Weijia Kong, Harvard Wai Hann Hui, Hui Peng, Wilson Wen Bin Goh · 2022 · PROTEOMICS
34. Forecasting carbon price trends based on an interpretable light gradient boosting machine and Bayesian optimization
    Shangkun Deng, Jiankang Su, Yingke Zhu, Yiting Yu, Chongyi Xiao · 2023 · Expert Systems with Applications
35. The global fate of inorganic phosphorus fertilizers added to terrestrial ecosystems
    Xianzhen Luo, Ahmed Salah Elrys, Lingling Zhang, Muhammed Mustapha Ibrahim, Yang Liu, Shenglei Fu, Junhua Yan, Qing Ye, Dazhi Wen, Enqing Hou · 2024 · One Earth
36. Prediction with missing data via Bayesian Additive Regression Trees
    Adam D. Kapelner, Justin Bleich · 2015 · Canadian Journal of Statistics
37. A genetic algorithm approach to optimising random forests applied to class engineered data
    Eyad Elyan, Mohamed Medhat Gaber · 2016 · Information Sciences
38. Can Machine-learning Techniques Be Used for 5-year Survival Prediction of Patients With Chondrosarcoma?
    Quirina C. B. S. Thio, Aditya V. Karhade, Paul T. Ogink, Kevin A. Raskin, Karen De Amorim Bernstein, Santiago A. Lozano‐Calderón, Joseph Hasbrouck Schwab · 2018 · Clinical Orthopaedics and Related Research
39. External Validation of the SORG 90-day and One-Year Machine Learning Algorithms for Survival in Spinal Metastatic Disease.
    A. Karhade, A. Ahmed, Z. Pennington, A. Chara, Andrew T. Schilling, Q. Thio, P. Ogink, D. Sciubba, J. Schwab · 2019 · The spine journal
40. Multidisciplinary Pattern Recognition applications: A review
    Marina Paolanti, Emanuele Frontoni · 2020 · Computer Science Review
41. Fracture risk and height: An association partly accounted for by cortical porosity of relatively thinner cortices
    Åshild Bjørnerem, Minh Bui, Ali Ghasemzadeh, John Llewelyn Hopper, Roger Martin Djoumessi Zebaze, Ego Seeman · 2013 · Journal of Bone and Mineral Research
42. Feline calicivirus and other respiratory pathogens in cats with Feline calicivirus-related symptoms and in clinically healthy cats in Switzerland
    Alice Berger, Barbara Willi, Marina Luisa Meli, Felicitas S. Boretti, Sonja Hartnack, Anou Dreyfus, Hans Lutz, Regina Hofmann‐Lehmann · 2015 · BMC Veterinary Research
43. Multivariate Genomic Selection and Potential of Rapid Indirect Selection with Speed Breeding in Spring Wheat
    Amy Watson, Lee Thomas Hickey, Jack Christopher, Jessica Elaine Rutkoski, Jesse Poland, Ben J. Hayes · 2019 · Crop Science
44. Microbiota long-term dynamics and prediction of acute graft-versus-host disease in pediatric allogeneic stem cell transplantation
    Anna Cäcilia Ingham, Katrine Kielsen, Hanne Mordhorst, Marianne Ifversen, Frank M. Aarestrup, Klaus Müller, Sünje Johanna Pamp · 2021 · Microbiome
45. Prevalence and Prognostic Implications of Diabetes With Cardiomyopathy in Community-Dwelling Adults
    Matthew W. Segar, Muhammad Shahzeb Khan, Kershaw V. Patel, Javed Butler, W.H. Wilson Tang, Muthiah Vaduganathan, Carolyn S.P. Lam, Subodh Verma, Darren K. McGuire, Ambarish Pandey · 2021 · Journal of the American College of Cardiology
46. Effects of plant diversity on productivity strengthen over time due to trait-dependent shifts in species overyielding
    Liting Zheng, Kathryn E. Barry, Nathaly R. Guerrero‐Ramírez, Dylan Craven, Peter B. Reich, Kris Verheyen, Michael Scherer‐Lorenzen, Nico Eisenhauer, Nadia Barsoum, Jürgen Bauhus et al. · 2024 · Nature Communications
47. Machine Learning Approaches in Polymer Science: Progress and Fundamental for a New Paradigm
    Chunhui Xie, Haoke Qiu, Lu Liu, Yang You, Hongfei Li, Yunqi Li, Zhao‐Yan Sun, Jiaping Lin, Lijia An · 2025 · SmartMat
48. Eggplant Resistance to the Ralstonia solanacearum Species Complex Involves Both Broad-Spectrum and Strain-Specific Quantitative Trait Loci
    Sylvia Salgon, Cyril Jourda, Christopher Sauvage, Marie‐Christine Daunay, Bernard Reynaud, Emmanuel Wicker, Jacques Dintinger · 2017 · Frontiers in Plant Science
49. Discovery and Validation of a Urinary Exosome mRNA Signature for the Diagnosis of Human Kidney Transplant Rejection
    Rania El Fekih, James D. Hurley, Vasisht R. Tadigotla, Areej saud a Alghamdi, Anand Srivastava, Christine M. Coticchia, John Yongjoon Choi, Hazim Allos, Karim M. Yatim, Juliano B. Alhaddad et al. · 2021 · Journal of the American Society of Nephrology
50. Automatic gap-filling of daily streamflow time series in data-scarce regions using a machine learning algorithm
    Pedro Arriagada, Bruno Karelovic, Óscar Link · 2021 · Journal of Hydrology
51. Tree-based machine learning model for visualizing complex relationships between biochar properties and anaerobic digestion
    Yi Zhang, Yijing Feng, Zhonghao Ren, Runguo Zuo, Tianhui Zhang, Yeqing Li, Yajing Wang, Zhiyang Liu, Ziyan Sun, Yongming M Han et al. · 2023 · Bioresource Technology
52. Tree-based prediction on incomplete data using imputation or surrogate decisions
    Holger Cevallos-Valdiviezo, Stefan Van Aelst · 2015 · Information Sciences
53. A Comparison of Imputation Strategies for Ordinal Missing Data on Likert Scale Variables
    Wei Wu, Fan Jia, Craig K. Enders · 2015 · Multivariate Behavioral Research
54. Generative adversarial networks for imputing missing data for big data clinical research
    Weinan Dong, Dyt Fong, Jin-sun Yoon, Eric Yuk Fai Wan, Laura Elizabeth Bedford, Eric Ho Man Tang, Cindy Lo Kuen Lam · 2021 · BMC Medical Research Methodology
55. Predictions of heading date in bread wheat (Triticum aestivum L.) using QTL-based parameters of an ecophysiological model
    Bogard, M., Ravel, C., Paux, E., Bordes, J., Balfourier, F., Chapman, S. C., Le Gouis, J., Allard, V. · 2014 · Journal of Experimental Botany
56. Simultaneous selection for grain yield and protein content in genomics-assisted wheat breeding
    Sebastian Michel, Franziska Löschenberger, Christian Ametz, Bernadette Pachler, Ellen Sparry, Hermann Buerstmayr · 2019 · Theoretical and Applied Genetics
57. A Machine Learning Approach to Predicting Diabetes Complications
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58. Fault Detection and Classification in Industrial IoT in Case of Missing Sensor Data
    Merim Dzaferagic, Nicola Marchetti, Irene Macaluso B · 2021 · IEEE Internet of Things Journal
59. The evolution of insular woodiness
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60. Is Left Ventricular Systolic Dysfunction Associated With Increased Mortality Among Patients With Sepsis and Septic Shock?
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61. Applying network analysis to psychological comorbidity and health behavior: Depression, PTSD, and sexual risk in sexual minority men with trauma histories.
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62. Determinants of frailty development and progression using a multidimensional frailty index: Evidence from the English Longitudinal Study of Ageing
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63. The effects of performance status one week before hospital admission on the outcomes of critically ill patients
    Fernando Godinho Zampieri, Fernando A. Bozza, Giulliana Martines Moralez, Débora Dutra da Silveira Mazza, Alexandre Vaz Scotti, Marcelo S. Santino, Rubens Ribeiro, Édison Moraes Rodrigues Filho, Maurício Magalhães Cabral, Marcelo O. Maia et al. · 2016 · Intensive Care Medicine
64. The Impact of Residual Mitral Regurgitation After MitraClip Therapy in Functional Mitral Regurgitation
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65. Using phylogenetic information to impute missing functional trait values in ecological databases
    Vanderlei Júlio Debastiani, Vinícius A. G. Bastazini, Valério D. Pillar · 2021 · Ecological Informatics
66. Individual treatment selection for patients with posttraumatic stress disorder
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67. Safety and efficacy of sonothrombolysis for acute ischaemic stroke: a multicentre, double-blind, phase 3, randomised controlled trial
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68. A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression
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69. Improving the baking quality of bread wheat by genomic selection in early generations
    Sebastian Michel, Christian Kummer, Martin Gallee, Jakob Hellinger, Christian Ametz, Batuhan Akgöl, Doru Gabriel Epure, Franziska Löschenberger, Hermann Buerstmayr · 2017 · Theoretical and Applied Genetics
70. Diverging functional strategies but high sensitivity to an extreme drought in tropical dry forests
    Roy González‐M., Juan Manuel Posada, Carlos P. Carmona, Fabián Garzón, Viviana Salinas, Álvaro Idárraga, Camila Pizano, Andrés Avella, René López Camacho, Natalia Norden-M et al. · 2020 · Ecology Letters
71. Missing Data Imputation: A Comprehensive Review
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72. Identification of loci controlling forage yield and nutritive value in diploid alfalfa using GBS-GWAS
    Muhammet Şakiroğlu, E. Charles Brummer · 2016 · Theoretical and Applied Genetics
73. Improving Risk Identification of Adverse Outcomes in Chronic Heart Failure Using SMOTE+ENN and Machine Learning
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74. NAM: association studies in multiple populations
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75. Reduced risk of pancreatic cancer associated with asthma and nasal allergies
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76. Work stress associated cool down reactions among nurses and hospital physicians and their relation to burnout symptoms
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77. Recent progress in alfalfa (Medicago sativa L.) genomics and genomic selection
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79. Maternal prenatal psychological distress and hair cortisol levels associate with infant fecal microbiota composition at 2.5 months of age
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80. Extinction of threatened vertebrates will lead to idiosyncratic changes in functional diversity across the world
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81. The immune factors driving DNA methylation variation in human blood
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86. Predictors of Deceased Donor Kidney Discard in the United States
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92. Multi-objective genetic algorithm for missing data imputation
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94. missForest: Nonparametric Missing Value Imputation using Random Forest
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95. Introduction bias affects relationships between the characteristics of ornamental alien plants and their naturalization success
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96. Consequences of multiple imputation of missing standard deviations and sample sizes in meta‐analysis
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97. Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments
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98. PC-GAIN: Pseudo-label conditional generative adversarial imputation networks for incomplete data
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99. Roadkill patterns in Latin American birds and mammals
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