Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI | Paper Citation Record

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Unresolved cited work

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This paper cites A benchmark for interpretability methods in deep neural networks.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI A benchmark for interpretability methods in deep neural networks

Reference 2

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This paper cites A benchmark for neural network robustness in skin cancer classification.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI A benchmark for neural network robustness in skin cancer classification

Reference 3

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This paper cites Robustness of convolutional neural networks in recognition of pigmented skin lesions.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Robustness of convolutional neural networks in recognition of pigmented skin lesions

Reference 4

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This paper cites White paper on artificial intelligence - a european approach to excellence and trust, 2020.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI White paper on artificial intelligence - a european approach to excellence and trust, 2020

Reference 5

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This paper cites Making the black box more transparent: Understanding the physical implications of machine learning.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Making the black box more transparent: Understanding the physical implications of machine learning

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This paper cites Toms, Elizabeth A.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Toms, Elizabeth A

Reference 7

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This paper cites Attention-based interpretable neural network for building cooling load prediction.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Attention-based interpretable neural network for building cooling load prediction

Reference 8

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This paper cites Interpretable neural network via algorithm unrolling for mechanical fault diagnosis.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Interpretable neural network via algorithm unrolling for mechanical fault diagnosis

Reference 9

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI General pitfalls of model-agnostic interpretation methods for machine learning models

Reference 10

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Methods for interpreting and understanding deep neural networks

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This paper cites Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC).

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)

Reference 12

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Unresolved cited work

Reference 13

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Deep learning applications for iot in health care: A systematic review

Reference 14

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI A guide to deep learning in healthcare

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This paper cites Recent deep learning techniques, challenges and its applications for medical healthcare system: a review.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Recent deep learning techniques, challenges and its applications for medical healthcare system: a review

Reference 16

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Deep learning in healthcare

Reference 17

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This paper cites From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare

Reference 18

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This paper cites Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare.

Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare

Reference 19

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Leveraging deep learning for designing healthcare analytics heuristic for diagnostics

Reference 20

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Learning deep features for discriminative localization

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Grad-cam++: General- ized gradient-based visual explanations for deep convolutional networks

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Opti-cam: Optimizing saliency maps for interpretability

Reference 23

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Deep residual learning for image recognition

Reference 24

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Melanoma detection using adversarial training and deep transfer learning

Reference 25

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Very Deep Convolutional Networks for Large-Scale Image Recognition

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI From attribution maps to human-understandable explanations through concept relevance propagation

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Evaluating the explainers: Black- box explainable machine learning for student success prediction in moocs

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Interpretcc: Intrinsic user-centric interpretability through global mixture of experts, 2024

Reference 30

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

Reference 31

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Unresolved cited work

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Ross Quinlan

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Decision trees

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI A novel hybrid classification model of artificial neural networks and multiple linear regression models

Reference 35

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning

Reference 36

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data

Reference 37

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Radial basis functions

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Radial basis function approximations: comparison and applications

Reference 39

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI This looks like that: deep learning for interpretable image recognition

Reference 40

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Protopshare: Prototypical parts sharing for similarity discovery in interpretable image classification

Reference 41

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI This looks like those: Illuminating prototypical concepts using multiple visualizations

Reference 42

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Softnet: A concept-controlled deep learning architecture for interpretable image classification

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI An inherently interpretable deep learning model for local explanations using visual concepts

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Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI Patchnet: Interpretable Neural Networks for Image Classification

Reference 45

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