Improving explanations for medical X-ray diagnosis combining variational autoencoders and adversarial machine learning
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad Politécnica de Madrid |
| Repositorio: | Archivo Digital UPM |
| OAI Identifier: | oai:dnet:archivodigit::f1925ef66443d9fe0a788fe1a6c4319b |
| Acceso en línea: | https://oa.upm.es/96255/ |
| Access Level: | acceso abierto |
| Palabra clave: | Adversarial learning Adversarial machine learning Adversarial optimisation Adversarial optimization Algorithm Algorithms Article Artificial Intelligence Auto encoders Autoencoder Cardiomegaly Classification Algorithm Classifier Comparative Study Computer Assisted Diagnosis Computer Vision deep learning DenseNet201 model Diagnosis EfficientNetB0 model Evolutionary Algorithm Explainable artificial intelligence False Positive Result Generative Adversarial Networks Genetic Algorithm Human Humans Image embedding Image Reconstruction Local linear Local linear modification Local linear modifications Machine Learning Machine-learning Medical computing Medical X-rays multi-output classification variational autoencoder network Mutation Rate Optimisations Radiodiagnosis Residual neural network ResNet50 model revertant Scoliosis Variational techniques VGG19 model X-ray diagnosis |
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