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Evaluating perceptual and semantic interpretability of saliency methods: A case study of melanoma

https://doi.org/10.1002/ail2.77
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/jama.292.22.2771openalex-snapshot
Early Diagnosis of Cutaneous Melanoma
inferredcites →https://doi.org/10.1006/cogp.1993.1006openalex-snapshot
Feature-Based Induction
inferredcites →https://doi.org/10.1007/978-3-030-20351-1_62openalex-snapshot
Melanoma Recognition via Visual Attention
inferredcites →https://doi.org/10.1007/978-3-319-10590-1_53openalex-snapshot
Visualizing and Understanding Convolutional Networks
inferredcites →https://doi.org/10.1016/j.ejca.2022.02.025openalex-snapshot
Explainable artificial intelligence in skin cancer recognition: A systematic review
inferredcites →https://doi.org/10.1016/j.inffus.2019.12.012openalex-snapshot
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
inferredcites →https://doi.org/10.1037//0033-295x.104.2.301openalex-snapshot
Making sense of randomness: Implicit encoding as a basis for judgment.
inferredcites →https://doi.org/10.1046/j.1365-2133.1998.02075.xopenalex-snapshot
Clinical accuracy of the diagnosis of cutaneous malignant melanoma
inferredcites →https://doi.org/10.1080/21681163.2021.2003248openalex-snapshot
Saliency-based segmentation of dermoscopic images using colour information
inferredcites →https://doi.org/10.1109/access.2018.2870052openalex-snapshot
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/iscc53001.2021.9631485openalex-snapshot
Exemplars and Counterexemplars Explanations for Image Classifiers, Targeting Skin Lesion Labeling
inferredcites →https://doi.org/10.1109/jstsp.2008.2011163openalex-snapshot
Image Feature Extraction in the Last Screening Mammograms Prior to Detection of Breast Cancer
inferredcites →https://doi.org/10.1109/tmi.2019.2899534openalex-snapshot
Direct Automatic Coronary Calcium Scoring in Cardiac and Chest CT
inferredcites →https://doi.org/10.1117/12.2585967openalex-snapshot
Explainable AI for medical imaging: explaining pneumothorax diagnoses with Bayesian teaching
inferredcites →https://doi.org/10.1145/2939672.2939778openalex-snapshot
"Why Should I Trust You?"
inferredcites →https://doi.org/10.1145/3233231openalex-snapshot
The Mythos of Model Interpretability
inferredcites →https://doi.org/10.1145/3236009openalex-snapshot
A Survey of Methods for Explaining Black Box Models
inferredcites →https://doi.org/10.1145/3447548.3467148openalex-snapshot
An Experimental Study of Quantitative Evaluations on Saliency Methods
inferredcites →https://doi.org/10.1148/ryai.2021200267openalex-snapshot
Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging
inferredcites →https://doi.org/10.1155/2018/1524286openalex-snapshot
Segmentation of Melanoma Skin Lesion Using Perceptual Color Difference Saliency with Morphological Analysis
inferredcites →https://doi.org/10.1177/0049124118782533openalex-snapshot
Fairness in Criminal Justice Risk Assessments: The State of the Art
inferredcites →https://doi.org/10.1186/s41747-018-0061-6openalex-snapshot
Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine
inferredcites →https://doi.org/10.1371/journal.pone.0234352openalex-snapshot
Towards the automatic detection of skin lesion shape asymmetry, color variegation and diameter in dermoscopic images
inferredcites →https://doi.org/10.1590/rbeb.2014.019openalex-snapshot
Lung disease detection using feature extraction and extreme learning machine
inferredcites →https://doi.org/10.1609/aimag.v40i2.2850openalex-snapshot
DARPA's Explainable Artificial Intelligence Program
inferredcites →https://doi.org/10.3322/canjclin.35.3.130openalex-snapshot
Early Detection of Malignant Melanoma: The Role of Physician Examination and Self-Examination of the Skin
inferredcites →https://doi.org/10.3390/jimaging6060052openalex-snapshot
Explainable Deep Learning Models in Medical Image Analysis
inferredcites →https://doi.org/10.48550/arxiv.1101.3354openalex-snapshot
Introduction to the Bag of Features Paradigm for Image Classification and Retrieval
inferredcites →https://doi.org/10.48550/arxiv.1605.01397openalex-snapshot
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)
inferredcites →https://doi.org/10.48550/arxiv.1806.07421openalex-snapshot
RISE: Randomized Input Sampling for Explanation of Black-box Models
inferredcites →https://doi.org/10.48550/arxiv.1806.07538openalex-snapshot
Towards Robust Interpretability with Self-Explaining Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1904.00760openalex-snapshot
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
inferredcites →https://doi.org/10.48550/arxiv.2009.07896openalex-snapshot
Captum: A unified and generic model interpretability library for PyTorch
inferredcites →https://doi.org/10.48550/arxiv.2012.15049openalex-snapshot
SkiNet: A Deep Learning Solution for Skin Lesion Diagnosis with Uncertainty Estimation and Explainability
inferredcites →https://doi.org/10.48550/arxiv.2111.11863openalex-snapshot
Explainable Deep Image Classifiers for Skin Lesion Diagnosis
inferredcites →https://doi.org/10.5853/jos.2017.02054openalex-snapshot
Deep into the Brain: Artificial Intelligence in Stroke Imaging
inferredcites →https://doi.org/10.7717/peerj.453openalex-snapshot
scikit-image: image processing in Python

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/cpe.70885openalex-snapshot
Explainable Deep Learning for Imaging‐Based Skin Lesion Diagnosis: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1002/widm.70075openalex-snapshot
Interpretable Machine Learning: A Comprehensive Review of Foundations, Methods, and the Path Forward
inferred← citeshttps://doi.org/10.1007/978-3-032-11381-8_2openalex-snapshot
Detection of Drug Abuse Through CNNs and ViTs: A Comparative Analysis of Performance and Explainability
inferred← citeshttps://doi.org/10.1007/s00256-025-04951-0openalex-snapshot
Optimizing the power of AI for fracture detection: from blind spots to breakthroughs
inferred← citeshttps://doi.org/10.1007/s13721-025-00709-9openalex-snapshot
Explainable transfer learning for skin cancer diagnosis
inferred← citeshttps://doi.org/10.1109/ssd64182.2025.10989876openalex-snapshot
Explainable Pre-Trained Models for Skin Cancer Classification
inferred← citeshttps://doi.org/10.1111/tops.12642openalex-snapshot
The Inner Loop of Collective Human–Machine Intelligence
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3151281/v1openalex-snapshot
Artificial Intelligence Reveals Distinct Prognostic Subgroups of Muscle-Invasive Bladder Cancer on Histology Images
inferred← citeshttps://doi.org/10.32473/flairs.38.1.138992openalex-snapshot
Measuring Interpretability: A systematic literature review of interpretability measures in artificial intelligence
inferred← citeshttps://doi.org/10.3390/asi8020035openalex-snapshot
Exploring Pre-Trained Models for Skin Cancer Classification
inferred← citeshttps://doi.org/10.3390/cancers15204998openalex-snapshot
Artificial Intelligence Reveals Distinct Prognostic Subgroups of Muscle-Invasive Bladder Cancer on Histology Images
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