Synthetic data in machine learning for medicine and healthcare | Nature Biomedical Engineering
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Synthetic data are becoming a critical tool for building artificially intelligent systems.
Simulators provide a way of generating data systematically and at scale. These data can …

There is a growing demand for the uptake of modern artificial intelligence technologies
within healthcare systems. Many of these technologies exploit historical patient health data …

For machine learning developers, the use of prediction tools in real-world clinical settings
can be a distant goal. Recently published guidelines for reporting clinical research that …

Background Machine learning (ML) has made a significant impact in medicine and cancer
research; however, its impact in these areas has been undeniably slower and more limited …

Abstract Machine learning techniques in healthcare use the increasing amount of health
data provided by the Internet of Things to improve patient outcomes. These techniques …

Several sources of bias can affect the performance of machine learning systems used in
medicine and potentially impact clinical care. Here, we discuss solutions to mitigate bias …

Electronic healthcare record data have been used to study risk factors of disease, treatment
effectiveness and safety, and to inform healthcare service planning. There has been …

Steps to avoid overuse and misuse of machine learning in clinical research | Nature Medicine
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Direct-to-consumer medical artificial intelligence/machine learning applications are
increasingly used for a variety of diagnostic assessments, and the emphasis on …