AIMC Topic: Random Forest

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Random Forest Prognostication of Survival and 6-Month Outcome in Pediatric Patients Following Decompressive Craniectomy for Traumatic Brain Injury.

World neurosurgery Nov 15, 2024
BACKGROUND: There is a dearth of literature regarding prognostic and predictive factors for outcome following pediatric decompressive craniectomy (DC) performed after traumatic brain injury (TBI). The aim of this study was to develop a random forest ...
Infant Adolescent Child, Preschool Child Hospital Mortality Treatment Outcome Brain Injuries, Traumatic Random Forest Prognosis Retrospective Studies Female Glasgow Outcome Scale Male Decompressive Craniectomy Humans Machine Learning
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Water environment risk prediction method based on convolutional neural network-random forest.

Marine pollution bulletin Nov 13, 2024
The accelerated processes of urbanization and industrialization globally have resulted in an increased risk to aquatic environments, posing a significant threat to the sustainable management of water resources and the health of ecosystems. Accurate p...
China Environmental Monitoring Random Forest Neural Networks, Computer Ecosystem Risk Assessment
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Improving methylmalonic acidemia (MMA) screening and MMA genotype prediction using random forest classifier in two Chinese populations.

European journal of medical research Nov 10, 2024
BACKGROUND: Methylmalonic acidemia (MMA) is one of the most common hereditary organic acid metabolism disorders that endangers the lives and health of infants and children. Early detection and intervention before the appearance of a newborn's clinica...
Humans China Genotype East Asian People Random Forest Machine Learning Female Infant, Newborn Male Neonatal Screening Amino Acid Metabolism, Inborn Errors
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MGCNRF: Prediction of Disease-Related miRNAs Based on Multiple Graph Convolutional Networks and Random Forest.

IEEE transactions on neural networks and learning systems Oct 29, 2024
Increasing microRNAs (miRNAs) have been confirmed to be inextricably linked to various diseases, and the discovery of their associations has become a routine way of treating diseases. To overcome the time-consuming and laborious shortcoming of tradit...
Algorithms Computational Biology Humans MicroRNAs Random Forest Neural Networks, Computer Disease
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Autism Spectrum Disorder and Atypical Brain Connectivity: Novel Insights from Brain Connectivity-Associated Genes by Combining Random Forest and Support Vector Machine Algorithm.

Omics : a journal of integrative biology Oct 17, 2024
It is estimated that approximately one in every 100 children is diagnosed with autism spectrum disorder (ASD) around the globe. Currently, there are no curative pharmacological treatments for ASD. Discoveries on key molecular mechanisms of ASD are es...
Autism Spectrum Disorder Brain Gene Expression Profiling Transcriptome Humans Algorithms Support Vector Machine Random Forest
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Using random forest and biomarkers for differentiating COVID-19 and Mycoplasma pneumoniae infections.

Scientific reports Sep 30, 2024
The COVID-19 pandemic has underscored the critical need for precise diagnostic methods to distinguish between similar respiratory infections, such as COVID-19 and Mycoplasma pneumoniae (MP). Identifying key biomarkers and utilizing machine learning t...
Mycoplasma pneumoniae Aged ROC Curve Biomarkers Humans Coinfection Adult Diagnosis, Differential Machine Learning Retrospective Studies Random Forest Male Procalcitonin COVID-19 Female Leukocyte Count C-Reactive Protein SARS-CoV-2 Middle Aged Pneumonia, Mycoplasma Interleukin-6
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Plant-based egg washes for use in baked goods: Machine learning and visual parameter analysis.

Journal of food science Sep 27, 2024
Pea protein is one potential environmentally sustainable way of recreating the functionality of eggs in coatings for baked goods. These coatings are commonly applied to enhance visual properties of baked goods that consumers desire, especially color ...
Pattern Recognition, Visual Pisum sativum Neural Networks, Computer Machine Learning Time Factors Hydrogen-Ion Concentration Principal Component Analysis Plant Proteins Color Cooking Eggs Glycerol Random Forest
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A hybrid approach for modeling bicycle crash frequencies: Integrating random forest based SHAP model with random parameter negative binomial regression model.

Accident; analysis and prevention Sep 16, 2024
To effectively capture and explain complex, nonlinear relationships within bicycle crash frequency data and account for unobserved heterogeneity simultaneously, this study proposes a new hybrid framework that combines the Random Forest-based SHapley ...
Regression Analysis Bayes Theorem Random Forest Accidents, Traffic London Bicycling Algorithms Risk Factors Support Vector Machine Models, Statistical Humans Machine Learning
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DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest.

Methods (San Diego, Calif.) Sep 11, 2024
Interactions of biological molecules in organisms are considered to be primary factors for the lifecycle of that organism. Various important biological functions are dependent on such interactions and among different kinds of interactions, the protei...
Neural Networks, Computer Algorithms Binding Sites Sequence Analysis, Protein Deep Learning DNA Protein Binding Random Forest Computational Biology DNA-Binding Proteins Databases, Protein Amino Acid Sequence
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A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.

JAMA health forum Sep 6, 2024
IMPORTANCE: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (...
Emergency Use Authorization Adolescent Antibodies, Viral Health Policy Antibodies, Monoclonal Adult Random Forest Male Humans SARS-CoV-2 United States Food and Drug Administration Middle Aged Machine Learning Hospitalization COVID-19 Drug Treatment Severity of Illness Index Aged COVID-19 Health Care Rationing Young Adult Retrospective Studies Electronic Health Records Female
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