IMPORTANCE: The use of machine learning applications related to health is rapidly increasing and may have the potential to profoundly affect the field of health care.
"Prepare Yourselves, Robots Will Soon Replace Doctors in Healthcare," screamed the headline in a 2017 Forbes magazine article. Media coverage like that makes it easy to see why artificial intelligence (AI) sounds like scary science fiction to some ph...
BACKGROUND: The integration of artificial intelligence (AI) into our digital healthcare system is seen as a significant strategy to contain Australia's rising healthcare costs, support clinical decision making, manage chronic disease burden and suppo...
Artificial Intelligence (AI) is evolving rapidly in healthcare, and various AI applications have been developed to solve some of the most pressing problems that health organizations currently face. It is crucial for health leaders to understand the s...
Artificial Intelligence (AI) is poised to revolutionize the way in which medicine is practiced and thereby transform how healthcare is delivered. While in its nascence in terms of medical applications, it is imperative that the healthcare community p...
BACKGROUND: In the last ten years, the international workshop on knowledge representation for health care (KR4HC) has hosted outstanding contributions of the artificial intelligence in medicine community pertaining to the formalization and representa...
Best practice & research. Clinical rheumatology
Aug 27, 2019
Digital health or eHealth technologies, notably pervasive computing, robotics, big-data, wearable devices, machine learning, and artificial intelligence (AI), have opened unprecedented opportunities as to how the diseases are diagnosed and managed wi...
BACKGROUND: Given the complexity of providing dementia care in hospitals, integrating technology into practice is a high challenge and an important opportunity. Although there are a growing demand and interest in using social robots in a variety of c...
Interest in machine-learning applications within medicine has been growing, but few studies have progressed to deployment in patient care. We present a framework, context and ultimately guidelines for accelerating the translation of machine-learning-...
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