Meta-ensemble learning with adaptive sampling for imbalanced medical Raman spectroscopy data

No abstract is available for this paper.

• Publication year

  2025

• Venue

  Applied Soft Computing

• Publication date

  2025-04-01

• Fields of study

  Chemistry, Medicine, Computer Science

• Identifiers
  DOI 10.1016/j.asoc.2025.113142
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A Molecular Typing Method for Invasive Breast Cancer by Serum Raman Spectroscopy.

  2024cited by this paper
• Enhancing Credit Card Fraud Detection: An Ensemble Machine Learning Approach

  2024cited by this paper
• A Comparative Study of SMOTE, Borderline-SMOTE, and ADASYN Oversampling Techniques using Different Classifiers

  2023cited by this paper
• A Survey on GAN Techniques for Data Augmentation to Address the Imbalanced Data Issues in Credit Card Fraud Detection

  2023cited by this paper
• Improvement Performance of the Random Forest Method on Unbalanced Diabetes Data Classification Using Smote-Tomek Link

  2023cited by this paper
• An efficient lightweight convolutional neural network for industrial surface defect detection

  2023cited by this paper
• Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning

  2023cited by this paper
• A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning

  2023cited by this paper
• RDDL: A systematic ensemble pipeline tool that streamlines balancing training schemes to reduce the effects of data imbalance in rare-disease-related deep-learning applications

  2023cited by this paper
• Application of Raman spectroscopy technology based on deep learning algorithm in the rapid diagnosis of glioma

  2022cited by this paper
• Deep reinforced neural network model for cyto-spectroscopic analysis of epigenetic markers for automated oral cancer risk prediction

  2022cited by this paper
• Accurate screening of early stage lung cancer based on improved ResNeXt model combined with serum Raman spectroscopy

  2022cited by this paper
• Assessment of skin inflammation using near-infrared Raman spectroscopy combined with artificial intelligence analysis in an animal model.

  2022cited by this paper
• Diagnosis of dengue virus infection using spectroscopic images and deep learning

  2022cited by this paper
• A micro-Raman spectroscopy study of inflammatory condition of human cervix: Probing of Tissues and blood plasma samples.

  2022cited by this paper
• A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method.

  2022cited by this paper
• An efficient fraud detection framework with credit card imbalanced data in financial services

  2022cited by this paper
• Raman spectroscopy and FTIR spectroscopy fusion technology combined with deep learning: A novel cancer prediction method.

  2022cited by this paper
• Benchmarking state-of-the-art imbalanced data learning approaches for credit scoring

  2022cited by this paper
• Scale-Adaptive Deep Model for Bacterial Raman Spectra Identification

  2021cited by this paper
• Machine Learning Based on Resampling Approaches and Deep Reinforcement Learning for Credit Card Fraud Detection Systems

  2021cited by this paper
• Raman optical identification of renal cell carcinoma via machine learning.

  2021cited by this paper
• Probabilistic Extension of Precision, Recall, and F1 Score for More Thorough Evaluation of Classification Models

  2020cited by this paper
• Rapid identification of cervical adenocarcinoma and cervical squamous cell carcinoma tissue based on Raman spectroscopy combined with multiple machine learning algorithms.

  2020cited by this paper
• Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting

  2019cited by this paper
• A survey on Image Data Augmentation for Deep Learning

  2019cited by this paper
• ENSEMBLE LEARNING DENGAN METODE SMOTEBAGGING PADA KLASIFIKASI DATA TIDAK SEIMBANG

  2018cited by this paper
• Smoothing Raman Spectra with Contiguous Single-Channel Fitting of Voigt Distributions: An Automated, High-Quality Procedure

  2018cited by this paper
• Logistic discrimination based on G-mean and F-measure for imbalanced problem

  2016cited by this paper
• The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

  2015cited by this paper
• RUSBoost: A Hybrid Approach to Alleviating Class Imbalance

  2010cited by this paper
• RAMOBoost: Ranked Minority Oversampling in Boosting

  2010cited by this paper
• Diversity analysis on imbalanced data sets by using ensemble models

  2009cited by this paper
• Advances in Raman Spectroscopy for Human Tissue

  2008cited by this paper
• Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning

  2005cited by this paper
• SMOTEBoost: Improving Prediction of the Minority Class in Boosting

  2003cited by this paper
• Automated Method for Subtraction of Fluorescence from Biological Raman Spectra

  2003cited by this paper
• SMOTE: Synthetic Minority Over-sampling Technique

  2002cited by this paper

• Fault diagnosis of inter-shaft bearings in small sample scenarios using multi-sensor spatio-temporal causal fusion and graph conditional variational adversarial networks

  2026cites this paper
• Physics-Constrained Twin Network: A Cross-Equipment Domain Adaptation Diagnosis Framework Based on Digital Twin Information Transfer

  2025cites this paper