16siThe 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-based support into new paradigms of care. Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows. We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support. We further find that AI-based multiclass probabilit...
In the past, the skills required to make an accurate dermatological diagnosis have required exposure...
Objective: Skin examination to detect cutaneous melanomas is commonly performed in primary care. In ...
Background: Thanks to the rapid development of computer-based systems and deep-learning-based algori...
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligenc...
This thesis investigates the use of Artificial Intelligence (AI) for skin cancer diagnosis. It explo...
Skin cancer continues to remain one of the major healthcare issues across the globe. If diagnosed ea...
Artificial intelligence (AI) based on machine learning and convolutional neuron networks (CNN) is ra...
A substantial body of research has been published on artificial intelligence applications in skin ca...
Background: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in d...
We investigated whether human preferences hold the potential to improve diagnostic artificial intell...
Background Skin cancers occur very commonly worldwide. Prognosis and disease burden are highly depen...
General practitioners (GPs) are playing a key role in skin cancer screening. Non-melanoma skin cance...
Abstract Background With rising incidence of skin cancer and relatively increased mortality rates, a...
Artificial intelligence (AI) algorithms for automated classification of skin diseases are available ...
Background: The use of different imaging modalities to assist in skin cancer diagnosis is a common ...
In the past, the skills required to make an accurate dermatological diagnosis have required exposure...
Objective: Skin examination to detect cutaneous melanomas is commonly performed in primary care. In ...
Background: Thanks to the rapid development of computer-based systems and deep-learning-based algori...
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligenc...
This thesis investigates the use of Artificial Intelligence (AI) for skin cancer diagnosis. It explo...
Skin cancer continues to remain one of the major healthcare issues across the globe. If diagnosed ea...
Artificial intelligence (AI) based on machine learning and convolutional neuron networks (CNN) is ra...
A substantial body of research has been published on artificial intelligence applications in skin ca...
Background: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in d...
We investigated whether human preferences hold the potential to improve diagnostic artificial intell...
Background Skin cancers occur very commonly worldwide. Prognosis and disease burden are highly depen...
General practitioners (GPs) are playing a key role in skin cancer screening. Non-melanoma skin cance...
Abstract Background With rising incidence of skin cancer and relatively increased mortality rates, a...
Artificial intelligence (AI) algorithms for automated classification of skin diseases are available ...
Background: The use of different imaging modalities to assist in skin cancer diagnosis is a common ...
In the past, the skills required to make an accurate dermatological diagnosis have required exposure...
Objective: Skin examination to detect cutaneous melanomas is commonly performed in primary care. In ...
Background: Thanks to the rapid development of computer-based systems and deep-learning-based algori...