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Literature DB >> 29440440

Classification and interaction in random forests.

Danielle Denisko^1,2, Michael M Hoffman^3,2,4.

Abstract

Mesh：

Year: 2018 PMID： 29440440 PMCID： PMC5828645 DOI： 10.1073/pnas.1800256115

Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN： 0027-8424 Impact factor: 11.205

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5 in total

1. Predicting in vitro drug sensitivity using Random Forests.

Authors: Gregory Riddick; Hua Song; Susie Ahn; Jennifer Walling; Diego Borges-Rivera; Wei Zhang; Howard A Fine
Journal: Bioinformatics Date: 2010-12-05 Impact factor: 6.937

2. Identification of DNA-binding proteins using structural, electrostatic and evolutionary features.

Authors: Guy Nimrod; András Szilágyi; Christina Leslie; Nir Ben-Tal
Journal: J Mol Biol Date: 2009-02-20 Impact factor: 5.469

3. Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?

Authors: Wouter G Touw; Jumamurat R Bayjanov; Lex Overmars; Lennart Backus; Jos Boekhorst; Michiel Wels; Sacha A F T van Hijum
Journal: Brief Bioinform Date: 2012-07-10 Impact factor: 11.622

4. Iterative random forests to discover predictive and stable high-order interactions.

Authors: Sumanta Basu; Karl Kumbier; James B Brown; Bin Yu
Journal: Proc Natl Acad Sci U S A Date: 2018-01-19 Impact factor: 11.205

5. Detection and localization of surgically resectable cancers with a multi-analyte blood test.

Authors: Joshua D Cohen; Lu Li; Yuxuan Wang; Christopher Thoburn; Bahman Afsari; Ludmila Danilova; Christopher Douville; Ammar A Javed; Fay Wong; Austin Mattox; Ralph H Hruban; Christopher L Wolfgang; Michael G Goggins; Marco Dal Molin; Tian-Li Wang; Richard Roden; Alison P Klein; Janine Ptak; Lisa Dobbyn; Joy Schaefer; Natalie Silliman; Maria Popoli; Joshua T Vogelstein; James D Browne; Robert E Schoen; Randall E Brand; Jeanne Tie; Peter Gibbs; Hui-Li Wong; Aaron S Mansfield; Jin Jen; Samir M Hanash; Massimo Falconi; Peter J Allen; Shibin Zhou; Chetan Bettegowda; Luis A Diaz; Cristian Tomasetti; Kenneth W Kinzler; Bert Vogelstein; Anne Marie Lennon; Nickolas Papadopoulos
Journal: Science Date: 2018-01-18 Impact factor: 47.728

5 in total

17 in total

1. A Random Forest Model for Predicting Social Functional Improvement in Chinese Patients with Schizophrenia After 3 Months of Atypical Antipsychotic Monopharmacy: A Cohort Study.

Authors: Yange Li; Lei Zhang; Yan Zhang; Hui Wen; Jingjing Huang; Yifeng Shen; Huafang Li
Journal: Neuropsychiatr Dis Treat Date: 2021-03-19 Impact factor: 2.570

2. Prediction of risk-associated genes and high-risk liver cancer patients from their mutation profile: benchmarking of mutation calling techniques.

Authors: Sumeet Patiyal; Anjali Dhall; Gajendra P S Raghava
Journal: Biol Methods Protoc Date: 2022-05-27

3. A Priori Estimation of the Narrow-Band UVB Phototherapy Outcome for Moderate-to-Severe Psoriasis Based on the Patients' Questionnaire and Blood Tests Using Random Forest Classifier.

Authors: Joanna Narbutt; Janusz Krzyścin; Piotr Sobolewski; Małgorzata Skibińska; Marcin Noweta; Witold Owczarek; Bonawentura Rajewska-Więch; Aleksandra Lesiak
Journal: Clin Cosmet Investig Dermatol Date: 2021-03-18

4. Machine learning as a strategy to account for dietary synergy: an illustration based on dietary intake and adverse pregnancy outcomes.

Authors: Lisa M Bodnar; Abigail R Cartus; Sharon I Kirkpatrick; Katherine P Himes; Edward H Kennedy; Hyagriv N Simhan; William A Grobman; Jennifer Y Duffy; Robert M Silver; Samuel Parry; Ashley I Naimi
Journal: Am J Clin Nutr Date: 2020-06-01 Impact factor: 8.472

Classification and interaction in random forests.

1. Predicting in vitro drug sensitivity using Random Forests.

2. Identification of DNA-binding proteins using structural, electrostatic and evolutionary features.

3. Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?

4. Iterative random forests to discover predictive and stable high-order interactions.

5. Detection and localization of surgically resectable cancers with a multi-analyte blood test.

1. A Random Forest Model for Predicting Social Functional Improvement in Chinese Patients with Schizophrenia After 3 Months of Atypical Antipsychotic Monopharmacy: A Cohort Study.

2. Prediction of risk-associated genes and high-risk liver cancer patients from their mutation profile: benchmarking of mutation calling techniques.

3. A Priori Estimation of the Narrow-Band UVB Phototherapy Outcome for Moderate-to-Severe Psoriasis Based on the Patients' Questionnaire and Blood Tests Using Random Forest Classifier.

4. Machine learning as a strategy to account for dietary synergy: an illustration based on dietary intake and adverse pregnancy outcomes.

5. Computational prediction of diagnosis and feature selection on mesothelioma patient health records.

6. Phylodynamic Analysis Complements Partner Services by Identifying Acute and Unreported HIV Transmission.

7. Machine Learning to Predict Contrast-Induced Acute Kidney Injury in Patients With Acute Myocardial Infarction.

8. Predictive modelling of hypoxic ischaemic encephalopathy risk following perinatal asphyxia.

9. Clinical characterization of dysautonomia in long COVID-19 patients.

10. Whole-Body Movement during Videogame Play Distinguishes Youth with Autism from Youth with Typical Development.