The use of machine learning (ML) and artificial intelligence (AI) in medical research continues to grow as the amount and availability of clinical data expands. These techniques allow complex interpretation of data and capture non-linear relations n...
AIM: To discuss ethical issues related to a complex study (PROFID) involving the development of a new, partly artificial intelligence-based, prediction model to enable personalised decision-making about the implantation of an implantable cardioverter...
Predicting and understanding how people make decisions has been a long-standing goal in many fields, with quantitative models of human decision-making informing research in both the social sciences and engineering. We show how progress toward this go...
Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical validation, device approval, and insurance coverage decisions of AI algorithms for medical diagnosis and p...
Journal of gastroenterology and hepatology
Feb 1, 2021
The future of gastrointestinal bleeding will include the integration of machine learning algorithms to enhance clinician risk assessment and decision making. Machine learning algorithms have shown promise in outperforming existing clinical risk score...
Inquiry : a journal of medical care organization, provision and financing
Jan 1, 2021
Cardiovascular diseases are one of the leading global causes of death. Following the positive experiences with machine learning in medicine we performed a study in which we assessed how machine learning can support decision making regarding coronary ...
We demonstrate that the key components of cognitive architectures (declarative and procedural memory) and their key capabilities (learning, memory retrieval, probability judgment, and utility estimation) can be implemented as algebraic operations on ...
Artificial moral agents raise complex ethical questions both in terms of the potential decisions they may make as well as the inputs that create their cognitive architecture. There are multiple differences between human and artificial cognition which...
Generative models provide a well-established statistical framework for evaluating uncertainty and deriving conclusions from large data sets especially in the presence of noise, sparsity, and bias. Initially developed for computer vision and natural l...
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