AIMC Topic: Machine Learning

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Robust Multiclass Feature Selection for the Authentication of Honey Botanical Origin via Nontargeted LC-MS Analysis.

Analytical chemistry Jun 11, 2025
Honey is one of the most frequently frauded foods due to the high market price of certain kinds of monofloral honey. Traditional authentication methods involving pollen or targeted analysis have limitations that can be manipulated by fraudsters. Nont...
Chromatography, Liquid Liquid Chromatography-Mass Spectrometry Honey Machine Learning Support Vector Machine Mass Spectrometry
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Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition state.

Science advances Jun 11, 2025
Amyloid aggregates are pathological hallmarks of many human diseases, but how soluble proteins nucleate to form amyloids is poorly understood. Here, we use combinatorial mutagenesis, a kinetic selection assay, and machine learning to massively pertur...
Humans Machine Learning Alzheimer Disease Mutation Amyloid beta-Peptides Protein Aggregates Kinetics Peptide Fragments Thermodynamics
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Diagnostic accuracy of machine learning-based magnetic resonance imaging models in breast cancer classification: a systematic review and meta-analysis.

World journal of surgical oncology Jun 11, 2025
OBJECTIVE: This meta-analysis evaluates the diagnostic accuracy of machine learning (ML)-based magnetic resonance imaging (MRI) models in distinguishing benign from malignant breast lesions and explores factors influencing their performance.
Magnetic Resonance Imaging Humans Female Machine Learning Sensitivity and Specificity Breast Neoplasms
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28-day all-cause mortality in patients with alcoholic cirrhosis: a machine learning prediction model based on the MIMIC-IV.

Clinical and experimental medicine Jun 11, 2025
To develop and validate a machine learning prediction model for 28-day all-cause mortality in patients with alcoholic cirrhosis using data from the MIMIC-IV database. The data of 2134 patients diagnosed with alcoholic cirrhosis (AC) were obtained fro...
Liver Cirrhosis, Alcoholic Middle Aged ROC Curve Aged Humans Machine Learning Adult Female Male Risk Factors
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Next-Generation Sequencing-Based Testing Among Patients With Advanced or Metastatic Nonsquamous Non-Small Cell Lung Cancer in the United States: Predictive Modeling Using Machine Learning Methods.

JMIR cancer Jun 11, 2025
BACKGROUND: Next-generation sequencing (NGS) has become a cornerstone of treatment for lung cancer and is recommended in current treatment guidelines for patients with advanced or metastatic disease.
Female Carcinoma, Non-Small-Cell Lung Humans Aged High-Throughput Nucleotide Sequencing Machine Learning Lung Neoplasms Adult Biomarkers, Tumor United States Male Middle Aged
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Preparing Tomorrow's Physicians: The Case for Machine Learning in Medical Education.

Journal of medical systems Jun 11, 2025
Machine learning should be integrated into medical curricula to prepare physicians-in-training for 21st-century practice conditions. This comment proposes practical implementation strategies that build upon existing educational frameworks by drawing ...
Machine Learning Humans Curriculum Education, Medical
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POC-CSP: a novel parameterised and orthogonally-constrained neural network layer for learning common spatial patterns (CSP) in EEG signals.

Journal of neural engineering Jun 11, 2025
. Common spatial patterns (CSPs) has been established as a powerful feature extraction method in EEG signal processing with machine learning, but it has shortcomings including sensitivity to noise and rigidity in the value of the weights. Our goal wa...
Electroencephalography Brain-Computer Interfaces Imagination Adult Male Humans Neural Networks, Computer Machine Learning
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Enhancing R-loop prediction with high-throughput sequencing data.

NAR genomics and bioinformatics Jun 11, 2025
R-loops are three-stranded RNA and DNA hybrid structures that often occur in the genome and play important roles in a variety of cellular processes from bacteria to mammals. Sequencing methods profiling R-loops genome-wide have revealed that they can...
Chromatin R-Loop Structures Humans Machine Learning Animals Mice High-Throughput Nucleotide Sequencing
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Extremity Soft Tissue Sarcoma Reconstruction Nomograms: A Clinicoradiomic, Machine Learning-Powered Predictor of Postoperative Outcomes.

JCO clinical cancer informatics Jun 11, 2025
PURPOSE: The choice of wound closure modality after limb-sparing extremity soft-tissue sarcoma (eSTS) resection is fraught with uncertainty. Leveraging machine learning and clinicoradiomic data, we developed Sarcoma Reconstruction Nomograms (SARCON),...
Humans Machine Learning Retrospective Studies Adult Male Middle Aged Female Aged Young Adult Soft Tissue Neoplasms Extremities Postoperative Complications Nomograms Treatment Outcome Plastic Surgery Procedures Sarcoma
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DeepSeek-AI-enhanced virtual reality training for mass casualty management: Leveraging machine learning for personalized instructional optimization.

PloS one Jun 11, 2025
OBJECTIVE: This study aimed to evaluate the effectiveness of a virtual reality (VR) training system for mass casualty management, integrating artificial intelligence (AI) and machine learning (ML) to analyze trainee performance and error patterns. Th...
Virtual Reality Mass Casualty Incidents Adult Male Humans Artificial Intelligence Machine Learning Female
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