AIMC Topic: Random Forest
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A Machine Learning Approach to Build and Evaluate a Molecular Prognostic Model for Endometrial Cancer Based on Tumour Microenvironment.
Journal of cellular and molecular medicine
Feb 1, 2025
Endometrial cancer (EC) incidence and the associated tumour burden have increased globally. To build a molecular expression prognostic model based on the tumour microenvironment to guide personalised treatment using a machine learning approach. Two d...
A two-stage forecasting model using random forest subset-based feature selection and BiGRU with attention mechanism: Application to stock indices.
PloS one
Jan 1, 2025
The heteroscedastic and volatile characteristics of stock price data have attracted the interest of researchers from various disciplines, particularly in the realm of price forecasting. The stock market's non-stationary and volatile nature, driven by...
Quality Assessment of Brain MRI Defacing Using Machine Learning.
Studies in health technology and informatics
Aug 22, 2024
Defacing of brain magnetic resonance imaging (MRI) scans is a crucial process in medical imaging research aimed at preserving patient privacy while maintaining data integrity. However, existing defacing algorithms are prone to errors, potentially com...
The Diagnosis of Cardiovascular Disease Using Simple Blood Biomarkers Through AI and Big Data.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Cardiovascular disease (CVD) is the leading cause of global mortality, diagnosed primarily through costly imaging modalities which are often overused in asymptomatic patients. Our project aims to develop an AI-based solution for CVD risk stratificati...
Exploring Random Forest Machine Learning for Fetal Movement Detection using Abdominal Acceleration and Angular Rate Data.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Fetal movement is a commonly monitored indicator of fetal wellbeing with reductions in fetal movement being associated with poor perinatal outcomes. However, more informative datasets of fetal movement are required for improved clinical decision maki...
What predicts citation counts and translational impact in headache research? A machine learning analysis.
Cephalalgia : an international journal of headache
May 1, 2024
BACKGROUND: We aimed to develop the first machine learning models to predict citation counts and the translational impact, defined as inclusion in guidelines or policy documents, of headache research, and assess which factors are most predictive.
Cross-subject EEG-based emotion recognition through dynamic optimization of random forest with sparrow search algorithm.
Mathematical biosciences and engineering : MBE
Feb 29, 2024
The objective of EEG-based emotion recognition is to classify emotions by decoding signals, with potential applications in the fields of artificial intelligence and bioinformatics. Cross-subject emotion recognition is more difficult than intra-subjec...
Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine.
Technology in cancer research & treatment
Jan 1, 2024
OBJECTIVE: This study presents a comparative analysis of RF and SVM for predicting calcein release from ultrasound-triggered, targeted liposomes under varied low-frequency ultrasound (LFUS) power densities (6.2, 9, and 10 mW/cm).
Exploitation of surrogate variables in random forests for unbiased analysis of mutual impact and importance of features.
Bioinformatics (Oxford, England)
Aug 1, 2023
MOTIVATION: Random forest is a popular machine learning approach for the analysis of high-dimensional data because it is flexible and provides variable importance measures for the selection of relevant features. However, the complex relationships bet...
Research on motion recognition based on multi-dimensional sensing data and deep learning algorithms.
Mathematical biosciences and engineering : MBE
Jul 5, 2023
Motion recognition provides movement information for people with physical dysfunction, the elderly and motion-sensing games production, and is important for accurate recognition of human motion. We employed three classical machine learning algorithms...
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