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 …
Shifting machine learning for healthcare from development to deployment and from models to data
In the past decade, the application of machine learning (ML) to healthcare has helped drive
the automation of physician tasks as well as enhancements in clinical capabilities and …
the automation of physician tasks as well as enhancements in clinical capabilities and …
Evaluation and mitigation of the limitations of large language models in clinical decision-making
Clinical decision-making is one of the most impactful parts of a physician's responsibilities
and stands to benefit greatly from artificial intelligence solutions and large language models …
and stands to benefit greatly from artificial intelligence solutions and large language models …
[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 …
Deep learning in histopathology: the path to the clinic
Abstract Machine learning techniques have great potential to improve medical diagnostics,
offering ways to improve accuracy, reproducibility and speed, and to ease workloads for …
offering ways to improve accuracy, reproducibility and speed, and to ease workloads for …
[HTML][HTML] Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks
Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …
diagnosis with their outstanding image classification performance. In spite of the outstanding …
Toward explainable artificial intelligence for precision pathology
The rapid development of precision medicine in recent years has started to challenge
diagnostic pathology with respect to its ability to analyze histological images and …
diagnostic pathology with respect to its ability to analyze histological images and …
[HTML][HTML] Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol
reporting by providing evidence-based recommendations for the minimum set of items to be …
reporting by providing evidence-based recommendations for the minimum set of items to be …
Deep learning in cancer pathology: a new generation of clinical biomarkers
Clinical workflows in oncology rely on predictive and prognostic molecular biomarkers.
However, the growing number of these complex biomarkers tends to increase the cost and …
However, the growing number of these complex biomarkers tends to increase the cost and …
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
The CONSORT 2010 statement provides minimum guidelines for reporting randomised
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …