A scoping review of reporting gaps in FDA-approved AI medical devices
V Muralidharan, BA Adewale, CJ Huang, MT Nta… - npj Digital …, 2024 - nature.com
Abstract Machine learning and artificial intelligence (AI/ML) models in healthcare may
exacerbate health biases. Regulatory oversight is critical in evaluating the safety and …
exacerbate health biases. Regulatory oversight is critical in evaluating the safety and …
[HTML][HTML] Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation
Abstract Trustworthy Artificial Intelligence (AI) is based on seven technical requirements
sustained over three main pillars that should be met throughout the system's entire life cycle …
sustained over three main pillars that should be met throughout the system's entire life cycle …
Medical artificial intelligence for clinicians: the lost cognitive perspective
The development and commercialisation of medical decision systems based on artificial
intelligence (AI) far outpaces our understanding of their value for clinicians. Although …
intelligence (AI) far outpaces our understanding of their value for clinicians. Although …
[HTML][HTML] Can ChatGPT provide intelligent diagnoses? A comparative study between predictive models and ChatGPT to define a new medical diagnostic bot
Intelligent diagnosis processes rely on Artificial Intelligence (AI) techniques to provide
possible diagnoses by analyzing patient data and medical information. To make accurate …
possible diagnoses by analyzing patient data and medical information. To make accurate …
Ignore, trust, or negotiate: understanding clinician acceptance of AI-based treatment recommendations in health care
Artificial intelligence (AI) in healthcare has the potential to improve patient outcomes, but
clinician acceptance remains a critical barrier. We developed a novel decision support …
clinician acceptance remains a critical barrier. We developed a novel decision support …
Solving the explainable AI conundrum by bridging clinicians' needs and developers' goals
Explainable artificial intelligence (XAI) has emerged as a promising solution for addressing
the implementation challenges of AI/ML in healthcare. However, little is known about how …
the implementation challenges of AI/ML in healthcare. However, little is known about how …
The prospect of artificial intelligence to personalize assisted reproductive technology
Abstract Infertility affects 1-in-6 couples, with repeated intensive cycles of assisted
reproductive technology (ART) required by many to achieve a desired live birth. In ART …
reproductive technology (ART) required by many to achieve a desired live birth. In ART …
Exploring the drivers of XAI-enhanced clinical decision support systems adoption: Insights from a stimulus-organism-response perspective
M Dalvi-Esfahani, M Mosharaf-Dehkordi… - … Forecasting and Social …, 2023 - Elsevier
Abstract The concept of Explainable Artificial Intelligence (XAI) provides a clear and
comprehensible explanation for the reasoning behind a system's output, allowing users to …
comprehensible explanation for the reasoning behind a system's output, allowing users to …
The role of artificial intelligence in improving patient outcomes and future of healthcare delivery in cardiology: a narrative review of the literature
D Gala, H Behl, M Shah, AN Makaryus - Healthcare, 2024 - mdpi.com
Cardiovascular diseases exert a significant burden on the healthcare system worldwide.
This narrative literature review discusses the role of artificial intelligence (AI) in the field of …
This narrative literature review discusses the role of artificial intelligence (AI) in the field of …
[HTML][HTML] Explainable Crowd Decision Making methodology guided by expert natural language opinions based on Sentiment Analysis with Attention-based Deep …
There exist a high demand to provide explainability to artificial intelligence systems, where
decision making models are included. This paper focuses on crowd decision making using …
decision making models are included. This paper focuses on crowd decision making using …