Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
Background and objectives Artificial intelligence (AI) has branched out to various
applications in healthcare, such as health services management, predictive medicine …
applications in healthcare, such as health services management, predictive medicine …
[HTML][HTML] AI recognition of patient race in medical imaging: a modelling study
Background Previous studies in medical imaging have shown disparate abilities of artificial
intelligence (AI) to detect a person's race, yet there is no known correlation for race on …
intelligence (AI) to detect a person's race, yet there is no known correlation for race on …
Obtaining genetics insights from deep learning via explainable artificial intelligence
Artificial intelligence (AI) models based on deep learning now represent the state of the art
for making functional predictions in genomics research. However, the underlying basis on …
for making functional predictions in genomics research. However, the underlying basis on …
AI in health and medicine
Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …
Multimodal deep learning for Alzheimer's disease dementia assessment
Worldwide, there are nearly 10 million new cases of dementia annually, of which
Alzheimer's disease (AD) is the most common. New measures are needed to improve the …
Alzheimer's disease (AD) is the most common. New measures are needed to improve the …
[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 …
[HTML][HTML] Transparency of deep neural networks for medical image analysis: A review of interpretability methods
Artificial Intelligence (AI) has emerged as a useful aid in numerous clinical applications for
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
[HTML][HTML] Deep learning for chest X-ray analysis: A survey
Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …
image analysis tasks. As the most commonly performed radiological exam, chest …
The medical algorithmic audit
Artificial intelligence systems for health care, like any other medical device, have the
potential to fail. However, specific qualities of artificial intelligence systems, such as the …
potential to fail. However, specific qualities of artificial intelligence systems, such as the …