Ecosyste.ms: Papers

An open API service providing mapping between scientific papers and software projects that are mentioned in them.
All mentions data is based on the CZI Software Mentions dataset.

Projects: cran: bartMachine

https://packages.ecosyste.ms/registries/cran.r-project.org/packages/bartMachine

Bayesian Additive Regression Trees
22 versions
Latest release: over 1 year ago
11 dependent packages
3,112 downloads last month

Papers Mentioning bartMachine 12

10.3390/ijms21062114

Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset
Cited by: 22
Author(s): Robert Ancuceanu, Marilena Viorica Hovaneț, Adriana Iuliana Anghel, Florentina Furtunescu, Monica Neagu, Carolina Constantin, Mihaela Dinu
Software Mentions: 24
Published: over 4 years ago

10.1371/journal.pone.0243467

Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study
Cited by: 16
Author(s): Frank Iorfino, Nicholas Ho, Joanne S. Carpenter, Shane Cross, Tracey A Davenport, Daniel F. Hermens, Hannah Yee, Alissa Nichles, Natalia Zmicerevska, Adam J. Guastella, Elizabeth Scott, Ian B. Hickie
Software Mentions: 14
Published: almost 4 years ago

10.3390/ijms21010019

Use of QSAR Global Models and Molecular Docking for Developing New Inhibitors of c-src Tyrosine Kinase
Cited by: 8
Author(s): Robert Ancuceanu, Bogdan Ionel Tamba, C. Stoicescu, Mihaela Dinu
Software Mentions: 13
Published: almost 5 years ago

10.1371/journal.pone.0135784

Comparison of Nine Statistical Model Based Warfarin Pharmacogenetic Dosing Algorithms Using the Racially Diverse International Warfarin Pharmacogenetic Consortium Cohort Database
Cited by: 38
Author(s): Rong Liu, Xi Li, Wei Zhang, Hong‐Hao Zhou
Software Mentions: 13
Published: about 9 years ago

10.1038/srep42192

Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients
Cited by: 86
Author(s): Jie Tang, Rong Liu, Yueli Zhang, Mou-Ze Liu, HU Yong-fang, Minghai Shao, Lan Zhu, Hua‐Wen Xin, Feng Gao, Wenjun Shang, Xiang‐Gao Meng, Lirong Zhang, Yingzi Ming, Wei Zhang
Software Mentions: 11
Published: almost 8 years ago

10.1186/s12940-017-0310-9

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES
Cited by: 73
Author(s): Sung Kyun Park, Zhangchen Zhao, Bhramar Mukherjee
Software Mentions: 9
Published: about 7 years ago

10.1002/jia2.25467

Super learner analysis of real‐time electronically monitored adherence to antiretroviral therapy under constrained optimization and comparison to non‐differentiated care approaches for persons living with HIV in rural Uganda
Cited by: 10
Author(s): Alejandra Benitez, Nicholas Musinguzi, David R. Bangsberg, Mwebesa Bwana, Conrad Muzoora, Peter W. Hunt, Jeffrey N. Martin, Jessica Haberer, Maya Petersen
Software Mentions: 9
Published: over 4 years ago

10.1155/2020/8810143

An Efficient and Effective Model to Handle Missing Data in Classification
Cited by: 8
Author(s): Kamran Mehrabani-Zeinabad, Marziyeh Doostfatemeh, Seyyed Mohammad Taghi Ayatollahi
Software Mentions: 6
Published: almost 4 years ago

10.18632/aging.203121

Identification of microenvironment related potential biomarkers of biochemical recurrence at 3 years after prostatectomy in prostate adenocarcinoma
Cited by: 9
Author(s): Xiaoru Sun, Lu Wang, Hongkai Li, Chuandi Jin, Yuanyuan Yu, Lei Hou, Xinhui Liu, Yifan Yu, Ran Yan, Fuzhong Xue
Software Mentions: 5
Published: over 3 years ago

10.3390/jcm8060865

The Role of Genetic Factors in Characterizing Extra-Intestinal Manifestations in Crohn’s Disease Patients: Are Bayesian Machine Learning Methods Improving Outcome Predictions?
Cited by: 10
Author(s): Daniele Bottigliengo, Paola Berchialla, Corrado Lanera, Danila Azzolina, Giulia Lorenzoni, Matteo Martinato, Daniela Giachino, Ileana Baldi, Darío Gregori
Software Mentions: 4
Published: over 5 years ago

10.1038/s41598-021-84781-x

Individualized prediction of COVID-19 adverse outcomes with MLHO
Cited by: 37
Author(s): Hossein Estiri, Zachary H. Strasser, Shawn N. Murphy
Software Mentions: 3
Published: over 3 years ago

10.1371/journal.pone.0207919

The UK Research Excellence Framework and the Matthew effect: Insights from machine learning
Cited by: 3
Author(s): Lloyd Balbuena
Software Mentions: 2
Published: almost 6 years ago