AIMC Topic: Random Forest

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Crossroads in Liver Transplantation: Is Artificial Intelligence the Key to Donor-Recipient Matching?

Medicina (Kaunas, Lithuania) Nov 28, 2022
Liver transplantation outcomes have improved in recent years. However, with the emergence of expanded donor criteria, tools to better assist donor-recipient matching have become necessary. Most of the currently proposed scores based on conventional b...
Neural Networks, Computer Artificial Intelligence Random Forest Liver Transplantation Tissue Donors Humans
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Multi-scale, domain knowledge-guided attention + random forest: a two-stage deep learning-based multi-scale guided attention models to diagnose idiopathic pulmonary fibrosis from computed tomography images.

Medical physics Nov 5, 2022
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible, and usually fatal lung disease of unknown reasons, generally affecting the elderly population. Early diagnosis of IPF is crucial for triaging patients' treatment planning...
Aged Deep Learning Random Forest Lung Diseases, Interstitial Idiopathic Pulmonary Fibrosis Retrospective Studies Tomography, X-Ray Computed Humans
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Predicting intersection crash frequency using connected vehicle data: A framework for geographical random forest.

Accident; analysis and prevention Nov 4, 2022
Accurate crash frequency prediction is critical for proactive safety management. The emerging connected vehicles technology provides us with a wealth of vehicular motion data, which enables a better connection between crash frequency and driving beha...
Geography Humans Artificial Intelligence Accidents, Traffic Automobile Driving Random Forest
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An evolutionary deep learning soft sensor model based on random forest feature selection technique for penicillin fermentation process.

ISA transactions Nov 2, 2022
Accurate and reliable measurement of key biological parameters during penicillin fermentation is of great significance for improving penicillin production. In this research context, a new hybrid soft sensor model method based on RF-IHHO-LSTM (random ...
Random Forest Fermentation Algorithms Penicillins Deep Learning
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Artificial intelligence models for clinical usage in dentistry with a focus on dentomaxillofacial CBCT: a systematic review.

Oral radiology Oct 21, 2022
This study aimed at performing a systematic review of the literature on the application of artificial intelligence (AI) in dental and maxillofacial cone beam computed tomography (CBCT) and providing comprehensive descriptions of current technical inn...
Spiral Cone-Beam Computed Tomography Random Forest Dentistry Artificial Intelligence Cone-Beam Computed Tomography
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Deep multi-task learning and random forest for series classification by pulse sequence type and orientation.

Neuroradiology Jul 30, 2022
PURPOSE: Increasingly complex MRI studies and variable series naming conventions reveal limitations of rule-based image routing, especially in health systems with multiple scanners and sites. Accurate methods to identify series based on image content...
Humans Neural Networks, Computer Random Forest Brain Magnetic Resonance Imaging
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Dementia risk predictions from German claims data using methods of machine learning.

Alzheimer's & dementia : the journal of the Alzheimer's Association Apr 22, 2022
INTRODUCTION: We examined whether German claims data are suitable for dementia risk prediction, how machine learning (ML) compares to classical regression, and what the important predictors for dementia risk are.
Insurance, Health Logistic Models Random Forest Machine Learning Humans Aged
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Predicting Procedure Step Performance From Operator and Text Features: A Critical First Step Toward Machine Learning-Driven Procedure Design.

Human factors Sep 28, 2020
OBJECTIVE: The goal of this study is to assess machine learning for predicting procedure performance from operator and procedure characteristics.
Logistic Models Algorithms Humans Random Forest ROC Curve Machine Learning
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Modeling student satisfaction in online learning using random forest.

Scientific reports Jul 2, 2025
The rapid expansion of online education has intensified the need to investigate the multifactorial determinants of university students' satisfaction with digital learning platforms. While prior studies have often examined technical or pedagogical com...
Adult Male Students Female Young Adult Machine Learning Personal Satisfaction Adolescent Learning Random Forest Universities Education, Distance Humans
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Predicting response to anti-VEGF therapy in neovascular age-related macular degeneration using random forest and SHAP algorithms.

Photodiagnosis and photodynamic therapy Jun 1, 2025
PURPOSE: This study aimed to establish and validate a prediction model based on machine learning methods and SHAP algorithm to predict response to anti-vascular endothelial growth factor (VEGF) therapy in neovascular age-related macular degeneration ...
Algorithms Retrospective Studies Female Humans Machine Learning Male Middle Aged Angiogenesis Inhibitors Aged Aged, 80 and over Wet Macular Degeneration Choroidal Neovascularization Vascular Endothelial Growth Factor A Macular Degeneration Photochemotherapy Tomography, Optical Coherence Random Forest
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