Keyphrases
Diagnostic Accuracy
100%
Skin Cancer Detection
100%
Machine Learning pipelines
100%
EfficientNet
100%
Feature Extraction
66%
F1 Score
66%
Computational Efficiency
66%
LightGBM
66%
Benign Skin Lesion
66%
Malignancy
33%
Early Detection
33%
Skin Cells
33%
DNA Damage
33%
5-fold Cross Validation
33%
Skin Cancer
33%
Improved Patient Outcomes
33%
Modularity
33%
State-of-the-art Techniques
33%
Test Accuracy
33%
Validation Accuracy
33%
Diagnostic System
33%
Ensemble Model
33%
Machine Learning Based
33%
ROC-AUC
33%
Training Accuracy
33%
Gradient Boosting
33%
Data Augmentation
33%
Learning-based Framework
33%
AUC Score
33%
Training pipeline
33%
Highly Aggressive
33%
Human Skin Cancer
33%
System Reliability
33%
Skin Cancer Classification
33%
Dataset Reliability
33%
INIS
detection
100%
accuracy
100%
pipelines
100%
machine learning
100%
skin cancer
100%
skin
40%
validation
40%
efficiency
40%
precision
40%
reliability
40%
datasets
40%
extraction
40%
data
20%
patients
20%
images
20%
solutions
20%
malignancies
20%
mutations
20%
dna damages
20%
performance
20%
classification
20%
auc
20%
augmentation
20%
Computer Science
Diagnostic Accuracy
100%
Computational Efficiency
100%
Machine Learning
100%
Learning System
100%
Feature Extraction
100%
Early Detection
50%
Fold Cross Validation
50%
Gradient Boosting
50%
Diagnostic System
50%
Data Augmentation
50%
Engineering
Feature Extraction
100%
Computational Efficiency
100%
Learning System
100%
System Diagnostics
50%
Early Detection
50%
State-of-the-Art Method
50%
Benign Case
50%
Malignant Case
50%
System Reliability
50%
Earth and Planetary Sciences
Pattern Recognition
100%
Machine Learning
100%
State of the Art
50%
Biochemistry, Genetics and Molecular Biology
Feature Extraction
100%
Solution and Solubility
50%
DNA Damage
50%
Cancer Classification
50%