OBJECTIVES: This study sought to develop and compare an array of machine learning methods to predict in-hospital mortality after transcatheter aortic valve replacement (TAVR) in the United States.
The journal of trauma and acute care surgery
Jul 1, 2019
BACKGROUND: Trauma has long been considered unpredictable. Artificial neural networks (ANN) have recently shown the ability to predict admission volume, acuity, and operative needs at a single trauma center with very high reliability. This model has ...
OBJECTIVES: With the transition to a value-based model of care delivery, bundled payment models have been implemented with demonstrated success in elective lower extremity joint arthroplasty. Yet, hip fracture outcomes are dependent on patient-level ...
The purpose of this study was to describe the current evidence found through a patent search about robotics used to assist nurses in providing care. The authors used a modified seven-step strategy of searching patents according to the US Patent and T...
BACKGROUND: Electronic health records (EHRs) are a rich source of health information; however social determinants of health, including incarceration, and how they impact health and health care disparities can be hard to extract.
BACKGROUND: Despite national screening efforts, military sexual trauma (MST) is underreported. Little is known of racial/ethnic differences in MST reporting in the Veterans Health Administration (VHA).
Artificial intelligence (AI) machines hold the world's curiosity captive. Futuristic television shows like West World are set in desert lands against pink sunsets where sleek, autonomous AI fulfill every human need, desire, and kink. But I, Robot, a ...
Journal of the American College of Radiology : JACR
Apr 1, 2019
Commercially available artificial intelligence (AI) algorithms outside of health care have been shown to be susceptible to ethnic, gender, and social bias, which has important implications in the development of AI algorithms in health care and the ra...
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