The clinician-AI interface: intended use and explainability in FDA-cleared AI devices for medical image interpretation
As applications of AI in medicine continue to expand, there is an increasing focus on
integration into clinical practice. An underappreciated aspect of this clinical translation is …
integration into clinical practice. An underappreciated aspect of this clinical translation is …
Guidelines and evaluation of clinical explainable AI in medical image analysis
Explainable artificial intelligence (XAI) is essential for enabling clinical users to get informed
decision support from AI and comply with evidence-based medical practice. Applying XAI in …
decision support from AI and comply with evidence-based medical practice. Applying XAI in …
AI in imaging: the regulatory landscape
DLG Hill - British Journal of Radiology, 2024 - academic.oup.com
Artificial intelligence (AI) methods have been applied to medical imaging for several
decades, but in the last few years, the number of publications and the number of AI-enabled …
decades, but in the last few years, the number of publications and the number of AI-enabled …
Trends in clinical validation and usage of US Food and Drug Administration-cleared artificial intelligence algorithms for medical imaging
AIM To examine the current landscape of US Food and Drug Administration (FDA)-approved
artificial intelligence (AI) medical imaging devices and identify trends in clinical validation …
artificial intelligence (AI) medical imaging devices and identify trends in clinical validation …
[HTML][HTML] The explainability paradox: Challenges for xAI in digital pathology
The increasing prevalence of digitised workflows in diagnostic pathology opens the door to
life-saving applications of artificial intelligence (AI). Explainability is identified as a critical …
life-saving applications of artificial intelligence (AI). Explainability is identified as a critical …
Explainable AI in medical imaging: An overview for clinical practitioners–Beyond saliency-based XAI approaches
K Borys, YA Schmitt, M Nauta, C Seifert… - European journal of …, 2023 - Elsevier
Driven by recent advances in Artificial Intelligence (AI) and Computer Vision (CV), the
implementation of AI systems in the medical domain increased correspondingly. This is …
implementation of AI systems in the medical domain increased correspondingly. This is …
[HTML][HTML] AI in diagnostic imaging: Revolutionising accuracy and efficiency
M Khalifa, M Albadawy - Computer Methods and Programs in Biomedicine …, 2024 - Elsevier
Introduction This review evaluates the role of Artificial Intelligence (AI) in transforming
diagnostic imaging in healthcare. AI has the potential to enhance accuracy and efficiency of …
diagnostic imaging in healthcare. AI has the potential to enhance accuracy and efficiency of …
Clinical Explainability Failure (CEF) & Explainability Failure Ratio (EFR)–changing the way we validate classification algorithms
VK Venugopal, R Takhar, S Gupta… - Journal of Medical Systems, 2022 - Springer
Abstract Adoption of Artificial Intelligence (AI) algorithms into the clinical realm will depend
on their inherent trustworthiness, which is built not only by robust validation studies but is …
on their inherent trustworthiness, which is built not only by robust validation studies but is …
The need for medical artificial intelligence that incorporates prior images
The use of artificial intelligence (AI) has grown dramatically in the past few years in the
United States and worldwide, with more than 300 AI-enabled devices approved by the US …
United States and worldwide, with more than 300 AI-enabled devices approved by the US …
The Crucial Role of Interdisciplinary Conferences in Advancing Explainable AI in Healthcare
As artificial intelligence (AI) integrates within the intersecting domains of healthcare and
computational biology, developing interpretable models tailored to medical contexts is met …
computational biology, developing interpretable models tailored to medical contexts is met …