AIMC Topic: Random Forest

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Long-Term Predictive Modelling of the Craniofacial Complex Using Machine Learning on 2D Cephalometric Radiographs.

International dental journal Jan 5, 2025
OBJECTIVE: This study aimed to predict long-term growth-related changes in skeletal and dental relationships within the craniofacial complex using machine learning (ML) models.
Humans Maxilla Skull Base Adolescent Development Predictive Learning Models Predictive Value of Tests Radiography Cephalometry Random Forest Face Random Allocation Child Incisor Mandible Body Size Puberty Retrospective Studies Regression Analysis Reproducibility of Results Male Adolescent
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Predicting autoimmune thyroiditis in primary Sjogren's syndrome patients using a random forest classifier: a retrospective study.

Arthritis research & therapy Jan 2, 2025
BACKGROUND: Primary Sjogren's syndrome (pSS) and autoimmune thyroiditis (AIT) share overlapping genetic and immunological profiles. This retrospective study evaluates the efficacy of machine learning algorithms, with a focus on the Random Forest Clas...
Humans Machine Learning Algorithms Retrospective Studies Middle Aged Female Autoantibodies Aged Random Forest Adult Sjogren's Syndrome Male Thyroiditis, Autoimmune
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A stacked CNN and random forest ensemble architecture for complex nursing activity recognition and nurse identification.

Scientific reports Dec 30, 2024
Nursing activity recognition has immense importance in the development of smart healthcare management and is an extremely challenging area of research in human activity recognition. The main reasons are an extreme class-imbalance problem and intra-cl...
Algorithms Humans Nurses Random Forest Neural Networks, Computer
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Finding the needle in the haystack of isokinetic knee data: Random Forest modelling improves information about ACLR-related deficiencies.

Journal of sports sciences Dec 22, 2024
The difficulties of rehabilitation after anterior cruciate ligament (ACL) injuries, subsequent return-to-sport (RTS) let alone achieving pre-injury performance, are well known. Isokinetic testing is often used to assess strength capacities during tha...
Random Forest Anterior Cruciate Ligament Injuries Anterior Cruciate Ligament Reconstruction Knee Hamstring Muscles Return to Sport Adult Biomechanical Phenomena Male Muscle Strength Humans Machine Learning Female Young Adult
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Improving prediction of solar radiation using Cheetah Optimizer and Random Forest.

PloS one Dec 20, 2024
In the contemporary context of a burgeoning energy crisis, the accurate and dependable prediction of Solar Radiation (SR) has emerged as an indispensable component within thermal systems to facilitate renewable energy generation. Machine Learning (ML...
Sunlight Logistic Models Support Vector Machine Random Forest Neural Networks, Computer Solar Energy Machine Learning Algorithms Forecasting
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Prediction of Two Year Survival Following Elective Repair of Abdominal Aortic Aneurysms at A Single Centre Using A Random Forest Classification Algorithm.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery Dec 9, 2024
OBJECTIVE: The decision to electively repair an abdominal aortic aneurysm (AAA) involves balancing the risk of rupture, peri-procedural death, and life expectancy. Random forest classifiers (RFCs) are powerful machine learning algorithms. The aim of ...
Aged Aged, 80 and over Male Middle Aged Algorithms Retrospective Studies Female Risk Factors Aortic Aneurysm, Abdominal Elective Surgical Procedures Random Forest Endovascular Procedures Risk Assessment Time Factors Treatment Outcome Predictive Value of Tests Humans Machine Learning
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Integrative analysis of PANoptosis-related genes in diabetic retinopathy: machine learning identification and experimental validation.

Frontiers in immunology Dec 4, 2024
BACKGROUND: Diabetic retinopathy (DR) is a major complication of diabetes, leading to severe vision impairment. Understanding the molecular mechanisms, particularly PANoptosis, underlying DR is crucial for identifying potential biomarkers and therape...
Gene Expression Regulation Molecular Targeted Therapy Memory T Cells Fatty Acid Synthase, Type I Humans Phospholipid Transfer Proteins Nomograms Diabetic Retinopathy Biomarkers Regulated Cell Death Human Umbilical Vein Endothelial Cells Machine Learning ROC Curve Random Forest RNA-Seq CD4-Positive T-Lymphocytes Gene Regulatory Networks
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Identification of a machine learning-based diagnostic model for axial spondyloarthritis in rheumatological routine care using a random forest approach.

RMD open Nov 27, 2024
OBJECTIVES: In axial spondyloarthritis (axSpA), early diagnosis is crucial, but diagnostic delay remains long and diagnostic criteria do not exist. We aimed to identify a diagnostic model that distinguishes patients with axSpA from patients without a...
Back Pain Axial Spondyloarthritis Algorithms Middle Aged Female ROC Curve Adult Random Forest Sensitivity and Specificity Early Diagnosis Male Humans Machine Learning
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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 ...
Humans Machine Learning Prognosis Retrospective Studies Brain Injuries, Traumatic Child, Preschool Random Forest Female Child Glasgow Outcome Scale Male Hospital Mortality Decompressive Craniectomy Infant Treatment Outcome Adolescent
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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...
Risk Assessment China Environmental Monitoring Random Forest Neural Networks, Computer Ecosystem
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