ArticleDiagnostics (Basel, Switzerland)2022
Melanoma Detection Using XGB Classifier Combined with Feature Extraction and K-Means SMOTE Techniques.
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 38 citations in OpenAlex.
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- A hybrid self attentive linearized phrase structured transformer based RNN for financial sentence analysis with sentence level explainability.Scientific reports · 2025Article
- Boosting skin cancer diagnosis accuracy with ensemble approach.Scientific reports · 2025Article
- AI-Driven Enhancement of Skin Cancer Diagnosis: A Two-Stage Voting Ensemble Approach Using Dermoscopic Data.Cancers · 2025Article
- Establishment of two pathomic-based machine learning models to predict CLCA1 expression in colon adenocarcinoma.PloS one · 2025Article
- Deeper insight into speech characteristics of patients at ultra-high risk using classification and explainability models.Frontiers in psychiatry · 2025Article
- Transformer-based decoder of melanoma classification using hand-crafted texture feature fusion and Gray Wolf Optimization algorithm.MethodsX · 2024Article
- Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique.World journal of gastrointestinal oncology · 2024Article
- Early Melanoma Detection Based on a Hybrid YOLOv5 and ResNet Technique.Diagnostics (Basel, Switzerland) · 2023Article
- VGG16 Feature Extractor with Extreme Gradient Boost Classifier for Pancreas Cancer Prediction.Journal of imaging · 2023Article
- Identification of colorectal cancer progression-associated intestinal microbiome and predictive signature construction.Journal of translational medicine · 2023Article
- Identification of intestinal microbiome associated with lymph-vascular invasion in colorectal cancer patients and predictive label construction.Frontiers in cellular and infection microbiology · 2023Article
- Analysis of cuproptosis-related genes in Ulcerative colitis and immunological characterization based on machine learning.Frontiers in medicine · 2023Article
- An Improved Endoscopic Automatic Classification Model for Gastroesophageal Reflux Disease Using Deep Learning Integrated Machine Learning.Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Melanoma, a very severe form of skin cancer, spreads quickly and has a high mortality rate if not treated early. Recently, machine learning, deep learning, and other related technologies have been successfully applied to computer-aided diagnostic tasks of skin lesions. However, some issues in terms of image feature extraction and imbalanced data need to be addressed. Based on a method for manually annotating image features by dermatologists, we developed a melanoma detection model with four improvement strategies, including applying the transfer learning technique to automatically extract image features, adding gender and age metadata, using an oversampling technique for imbalanced data, and comparing machine learning algorithms. According to the experimental results, the improved strategies proposed in this study have statistically significant performance improvement effects. In particular, our proposed ensemble model can outperform previous related models.
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