Optimized random forest model for predicting flexural properties of sustainable composites
Sign Up to like & getrecommendations! Published in 2024 at "Polymer Composites"
DOI: 10.1002/pc.28501
Abstract: In an era of technological advancements, the quest for sustainable products has taken a center stage. The utilization of natural fiber reinforced polymer composites has become crucial in the manufacturing of eco‐friendly products due to… read more here.
Keywords: flexural properties; forest model; random forest; polymer composites ... See more keywords
Permeability prediction method of unconsolidated sandstone reservoirs using CT scanning technology and random forest model
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Petroleum Exploration and Production Technology"
DOI: 10.1007/s13202-024-01852-1
Abstract: Developing unconsolidated sandstone reservoirs presents a formidable challenge due to their loose formation, which often triggers alterations in pore parameters and seepage characteristics during water injection processes. This study focuses on a specific reservoir, utilizing… read more here.
Keywords: sandstone reservoirs; permeability; forest model; unconsolidated sandstone ... See more keywords
Deep forest model for diagnosing COVID-19 from routine blood tests
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-95957-w
Abstract: The Coronavirus Disease 2019 (COVID-19) global pandemic has threatened the lives of people worldwide and posed considerable challenges. Early and accurate screening of infected people is vital for combating the disease. To help with the… read more here.
Keywords: deep forest; covid routine; forest model; model ... See more keywords
Classification of Bird and Drone Targets Based on Motion Characteristics and Random Forest Model Using Surveillance Radar Data
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3130231
Abstract: Accurate detection and tracking of birds and drones are of great significance in various low altitude airspace surveillance scenarios. Radar is currently the most proper long range surveillance technology for this problem but also challenged… read more here.
Keywords: surveillance; forest model; motion; classification ... See more keywords
Prediction of the Strength of Rubberized Concrete by an Evolved Random Forest Model
Sign Up to like & getrecommendations! Published in 2019 at "Advances in Civil Engineering"
DOI: 10.1155/2019/5198583
Abstract: Rubberized concrete (RC) has attracted more attention these years as it is an economical and environmental-friendly construction material. Normally, the uniaxial compressive strength (UCS) of RC needs to be evaluated before application. In this study,… read more here.
Keywords: strength; rubberized concrete; forest model; model ... See more keywords
Construction of Pulmonary Nodule CT Radiomics Random Forest Model Based on Artificial Intelligence Software for STAS Evaluation of Stage IA Lung Adenocarcinoma
Sign Up to like & getrecommendations! Published in 2022 at "Computational and Mathematical Methods in Medicine"
DOI: 10.1155/2022/2173412
Abstract: Objective Spread through air space (STAS) is an invasive characterization of lung adenocarcinoma and is regarded as a risk factor for poor prognosis. The aim of this study is to develop a random forest model… read more here.
Keywords: lung adenocarcinoma; lung; random forest; stage lung ... See more keywords
DCE-DForest: A Deep Forest Model for the Prediction of Anticancer Drug Combination Effects
Sign Up to like & getrecommendations! Published in 2022 at "Computational and Mathematical Methods in Medicine"
DOI: 10.1155/2022/8693746
Abstract: Drug combinations have recently been studied intensively due to their critical role in cancer treatment. Computational prediction of drug synergy has become a popular alternative strategy to experimental methods for anticancer drug synergy predictions. In… read more here.
Keywords: dce dforest; anticancer drug; deep forest; model ... See more keywords
Speeding up Myeloma Care: Robust Machine Learning Predictions of M-Spike Levels
Sign Up to like & getrecommendations! Published in 2024 at "Blood"
DOI: 10.1182/blood-2024-200888
Abstract: Introduction: Multiple myeloma (MM), a malignancy of plasma cells, poses diagnostic challenges due to its complex manifestations and variable outcomes. Accurate and rapid assessment of M-spike values is crucial for monitoring disease management . The… read more here.
Keywords: spike; forest model; spike values; random forest ... See more keywords
BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data
Sign Up to like & getrecommendations! Published in 2018 at "BMC Bioinformatics"
DOI: 10.1186/s12859-018-2095-4
Abstract: BackgroundThe classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning… read more here.
Keywords: classification; deep forest; forest model; model ... See more keywords
Analysis of factors influencing innovative behaviors of intensive care unit nurses using a random forest model-a multicentre cross-sectional study
Sign Up to like & getrecommendations! Published in 2025 at "BMC Nursing"
DOI: 10.1186/s12912-025-04052-2
Abstract: To identify and rank the key determinants-including sociodemographic factors, Spiritual Climate, Information Literacy, and Thriving at Work-of Innovative behaviours among intensive care nurses, and provide a theoretical basis for targeted interventions. Nurse innovation behavior is… read more here.
Keywords: care nurses; forest model; spiritual climate; random forest ... See more keywords
Prediction of Clinical Outcome at Discharge After Rupture of Anterior Communicating Artery Aneurysm Using the Random Forest Technique
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Neurology"
DOI: 10.3389/fneur.2020.538052
Abstract: Background: Aneurysmal subarachnoid hemorrhage (SAH) is a devastating disease. Anterior communicating artery (ACoA) aneurysm is the most frequent location of intracranial aneurysms. The purpose of this study is to predict the clinical outcome at discharge… read more here.
Keywords: outcome; rupture; forest model; anterior communicating ... See more keywords