Population and public health are in the midst of an artificial intelligence revolution capable of radically altering existing models of care delivery and practice. Just as AI seeks to mirror human cognition through its data-driven analytics, it can a...
Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Nov 19, 2021
There are well-recognized challenges to delivering specialty health care in rural settings. These challenges are particularly evident for specialized surgical health care due to the lack of trained operators in rural communities. Telerobotic surgery...
Adverse nursing events occur suddenly, unpredictably, or unexpectedly during course of clinical diagnosis and treatment processes in the hospitals. These events adversely affect the patient's diagnosis and treatment results and even increase the pati...
INTRODUCTION: Contemporary discourse on Artificial Intelligence (AI) in medicine is oft-sensationalised to the point of bearing no resemblance to its everyday impact and potential - either to proselytise it as a saviour or to condemn its perilous, am...
The concept of the cloud-to-thing continuum addresses advancements made possible by the widespread adoption of cloud, edge, and IoT resources. It opens the possibility of combining classical symbolic AI with advanced machine learning approaches in a ...
INTRODUCTION: Deep learning techniques are gaining momentum in medical research. Evidence shows that deep learning has advantages over humans in image identification and classification, such as facial image analysis in detecting people's medical cond...
Artificial intelligence (AI) has illuminated a clear path towards an evolving health-care system replete with enhanced precision and computing capabilities. Medical imaging analysis can be strengthened by machine learning as the multidimensional data...
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Nov 8, 2021
AIMS: This study aimed to investigate the application of infrared thermal imaging and adopt deep learning to detect air leakage for determining the fitness of respirators during fit-checks.
OBJECTIVE: To examine the role of explainability in machine learning for healthcare (MLHC), and its necessity and significance with respect to effective and ethical MLHC application.