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Bring on the Machines: Could Machine Learning Improve the Quality of Patient Education Materials? A Systematic Search and Rapid Review.

JCO clinical cancer informatics
PURPOSE: Clear and trustworthy information is essential for people who are ill. People with cancer, in particular, are targeted with vast quantities of patient education material, but of variable quality. Machine learning technologies are popular acr...

Adaptive semi-supervised recursive tree partitioning: The ART towards large scale patient indexing in personalized healthcare.

Journal of biomedical informatics
With the rapid development of information technologies, tremendous amount of data became readily available in various application domains. This big data era presents challenges to many conventional data analytics research directions including data ca...

Approximate dynamic programming approaches for appointment scheduling with patient preferences.

Artificial intelligence in medicine
During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the ...

An intelligent algorithm for identification of optimum mix of demographic features for trust in medical centers in Iran.

Artificial intelligence in medicine
Healthcare quality is affected by various factors including trust. Patients' trust to healthcare providers is one of the most important factors for treatment outcomes. The presented study identifies optimum mixture of patient demographic features wit...

How Should Clinicians Communicate With Patients About the Roles of Artificially Intelligent Team Members?

AMA journal of ethics
This commentary responds to a hypothetical case involving an assistive artificial intelligence (AI) surgical device and focuses on potential harms emerging from interactions between humans and AI systems. Informed consent and responsibility-specifica...