Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Feb 27, 2019
The term Artificial Intelligence (AI) was coined by John McCarthy in 1956 during a conference held on this subject. However, the possibility of machines being able to simulate human behavior and actually think was raised earlier by Alan Turing who de...
Health care organizations are leveraging machine-learning techniques, such as artificial neural networks (ANN), to improve delivery of care at a reduced cost. Applications of ANN to diagnosis are well-known; however, ANN are increasingly used to info...
BACKGROUND: Suicide is a national public health crisis and a critical patient safety issue. It is the 10th leading cause of death overall and the second leading cause of death among adolescents and young adults (15-34 years old). Research shows 80% o...
Computer methods and programs in biomedicine
Feb 1, 2019
BACKGROUND AND OBJECTIVE: Healthcare tweets are particularly challenging due to its sparse layout and its limited character size. Compared to previous method based on "bag of words" (BOW) model, this study uniquely identifies the enrichment protocol ...
Technology has enabled bionics and artificial intelligence, each of which can have important applications in health care. As we continue to substitute body parts with machinery, however, we might wonder, "What makes us human?" This drawing interrogat...
As with medicine, artistic practice has a historical relationship with technologies. As technology advances, artists and medical practitioners will struggle with the complexities of introducing artificial intelligence into pursuits that have long bee...
In June 2018, the American Medical Association adopted new policy to provide a broad framework for the evolution of artificial intelligence (AI) in health care that is designed to help ensure that AI realizes the benefits it promises for patients, ph...
BACKGROUND: As machine learning becomes increasingly common in health care applications, concerns have been raised about bias in these systems' data, algorithms, and recommendations. Simply put, as health care improves for some, it might not improve ...
Life sciences researchers using artificial intelligence (AI) are under pressure to innovate faster than ever. Large, multilevel, and integrated data sets offer the promise of unlocking novel insights and accelerating breakthroughs. Although more data...
Recent years have seen a surge of studies in machine learning in health and biomedicine, driven by digitalization of healthcare environments and increasingly accessible computer systems for conducting analyses. Many of us believe that these developme...