AIMC Topic: Random Forest

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Near-infrared spectroscopy assisted by random forest for predicting the physicochemical indicators of yak milk powder.

Food chemistry Mar 1, 2025
High-efficiency and cost-effective detection of physicochemical indicators is essential for the quality control of yak milk powder. Herein, a rapid and simultaneous detection method based on miniaturized near-infrared (NIR) spectroscopy and chemometr...
Milk Powders Milk Proteins Fats Animals Spectroscopy, Near-Infrared Cattle Random Forest Quality Control
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Machine-learning random forest algorithms predict post-cycloplegic myopic corrections from noncycloplegic clinical data.

Optometry and vision science : official publication of the American Academy of Optometry Feb 24, 2025
SIGNIFICANCE: Machine learning random forest algorithms were used to predict objective refractive outcomes after cycloplegic refraction using noncycloplegic clinical data. A classification model predicted post-cycloplegic myopia and could be useful i...
Female Young Adult Adult Cross-Sectional Studies Male Humans Machine Learning Algorithms Visual Acuity Random Forest Mydriatics Middle Aged Refraction, Ocular Myopia Adolescent
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Machine learning using random forest to differentiate between blow and fall situations of head trauma.

International journal of legal medicine Feb 22, 2025
Blunt head trauma is a common occurrence in forensic practice. Interpreting the origin of craniocerebral injuries can be a challenging process, particularly when it comes to distinguishing between falls or inflicted blows. The objective of this study...
Humans Machine Learning Female Aged Young Adult Adolescent Logistic Models Random Forest Skull Fractures Head Injuries, Closed Adult Male Middle Aged Accidental Falls
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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports.

PloS one Feb 13, 2025
This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. Firstly, the data collected in this study come fr...
Athletes Pattern Recognition, Automated Track and Field Humans Convolutional Neural Networks Machine Learning Support Vector Machine Computer Simulation Random Forest Biomechanical Phenomena Running
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Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer.

Scientific reports Feb 4, 2025
Gastric cancer (GC) is one of the most common tumors; one of the reasons for its poor prognosis is that GC cells can resist normal cell death process and therefore develop distant metastasis. Cuproptosis is a novel type of cell death and a limited nu...
Humans Machine Learning Gene Expression Regulation, Neoplastic Nomograms Random Forest Kaplan-Meier Estimate Male Middle Aged Gene Expression Profiling Transcriptome ROC Curve Prognosis Female Stomach Neoplasms Biomarkers, Tumor
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Pre-screening of endomysial microvessel density by fast random forest image processing machine learning algorithm accelerates recognition of a modified vascular network in idiopathic inflammatory myopathies.

Diagnostic pathology Jan 31, 2025
Biomarkers for discrimination among different subgroups of idiopathic inflammatory myopathies (IIM) are difficult to identify and may involve multiple laboratory tests and time-consuming procedures. We assessed the potential for artificial intelligen...
Microvascular Density Myositis Image Interpretation, Computer-Assisted Microvessels Platelet Endothelial Cell Adhesion Molecule-1 Capillaries Machine Learning Middle Aged Algorithms Image Processing, Computer-Assisted Female Muscle, Skeletal Humans Adult Random Forest Male
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Machine learning to detect recent recreational drug use in intensive cardiac care units.

Archives of cardiovascular diseases Jan 30, 2025
BACKGROUND: Although recreational drug use is a strong risk factor for acute cardiovascular events, systematic testing is currently not performed in patients admitted to intensive cardiac care units, with a risk of underdetection. To address this iss...
Predictive Value of Tests Substance-Related Disorders Random Forest Substance Abuse Detection Aged Humans France Illicit Drugs Male Machine Learning Coronary Care Units Middle Aged Prospective Studies Recreational Drug Use Risk Assessment Female Reproducibility of Results Risk Factors
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Machine Learning-Based Real-Time Survival Prediction for Gastric Neuroendocrine Carcinoma.

Annals of surgical oncology Jan 28, 2025
BACKGROUND: This study aimed to develop a dynamic survival prediction model utilizing conditional survival (CS) analysis and machine learning techniques for gastric neuroendocrine carcinomas (GNECs).
Humans Machine Learning Retrospective Studies Female Aged Stomach Neoplasms Survival Rate Male Predictive Learning Models Regression Analysis Middle Aged Random Forest Risk Assessment Carcinoma, Neuroendocrine Nomograms SEER Program United States Proportional Hazards Models
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Predicting postoperative adhesive small bowel obstruction in infants under 3 months with intestinal malrotation: a random forest approach.

Jornal de pediatria Jan 21, 2025
OBJECTIVE: This study aimed to develop a predictive model using a random forest algorithm to determine the likelihood of postoperative adhesive small bowel obstruction (ASBO) in infants under 3 months with intestinal malrotation.
Intestinal Volvulus Male Postoperative Complications Infant ROC Curve Predictive Value of Tests Tissue Adhesions Random Forest Intestinal Obstruction Retrospective Studies Intestine, Small Female Humans Infant, Newborn Risk Factors Machine Learning Sensitivity and Specificity Algorithms
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Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification.

PloS one Jan 16, 2025
Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die early. Though if it is detected in the early stages the patient has fairly good chance and the afore...
Random Forest Humans Neural Networks, Computer Algorithms Skin Neoplasms Deep Learning Convolutional Neural Networks Image Processing, Computer-Assisted Skin
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