[HTML][HTML] Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …
grows, especially in high-stakes decision making areas such as medical image analysis …
Explainable deep learning models in medical image analysis
Deep learning methods have been very effective for a variety of medical diagnostic tasks
and have even outperformed human experts on some of those. However, the black-box …
and have even outperformed human experts on some of those. However, the black-box …
Human–computer collaboration for skin cancer recognition
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial
intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI …
intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI …
A survey on explainable artificial intelligence (xai): Toward medical xai
Recently, artificial intelligence and machine learning in general have demonstrated
remarkable performances in many tasks, from image processing to natural language …
remarkable performances in many tasks, from image processing to natural language …
On interpretability of artificial neural networks: A survey
Deep learning as performed by artificial deep neural networks (DNNs) has achieved great
successes recently in many important areas that deal with text, images, videos, graphs, and …
successes recently in many important areas that deal with text, images, videos, graphs, and …
Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review
Abstract Transparency in Machine Learning (ML), often also referred to as interpretability or
explainability, attempts to reveal the working mechanisms of complex models. From a …
explainability, attempts to reveal the working mechanisms of complex models. From a …
Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international …
Background Whether machine-learning algorithms can diagnose all pigmented skin lesions
as accurately as human experts is unclear. The aim of this study was to compare the …
as accurately as human experts is unclear. The aim of this study was to compare the …
Checklist for evaluation of image-based artificial intelligence reports in dermatology: CLEAR derm consensus guidelines from the international skin imaging …
Importance The use of artificial intelligence (AI) is accelerating in all aspects of medicine and
has the potential to transform clinical care and dermatology workflows. However, to develop …
has the potential to transform clinical care and dermatology workflows. However, to develop …
[HTML][HTML] Explainable artificial intelligence in skin cancer recognition: A systematic review
K Hauser, A Kurz, S Haggenmüller, RC Maron… - European Journal of …, 2022 - Elsevier
Background Due to their ability to solve complex problems, deep neural networks (DNNs)
are becoming increasingly popular in medical applications. However, decision-making by …
are becoming increasingly popular in medical applications. However, decision-making by …
Dermoscopy image analysis: overview and future directions
Dermoscopy is a non-invasive skin imaging technique that permits visualization of features
of pigmented melanocytic neoplasms that are not discernable by examination with the …
of pigmented melanocytic neoplasms that are not discernable by examination with the …