Latest AI and machine learning research in prevention of medical errors for healthcare professionals.
OBJECTIVE: This study leveraged a state workers' compensation claims database and machine learning t...
BACKGROUND: Deaf people use sign or finger languages for communication, but these methods of communi...
This paper focuses on machine learning based voice conversion (VC) techniques for improving the spe...
RATIONALE: Central nervous system (CNS) aspergillosis has the characteristics of multifocality, poly...
At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in Septembe...
The majority of children with autism face difficulties in social interaction and communication skill...
HIV testing is the foundation for consolidated HIV treatment and prevention. In this study, we aim t...
Patient falls are a common safety event type that impairs the healthcare quality. Strategies includi...
Automated identification provides an efficient way to categorize patient safety incidents. Previous ...
To prevent deployment-related disorders, Chaos Driven Situations Management Retrieval System (CHARLY...
State-of-the-art neuron simulators are capable of simulating at most few tens/hundreds of neurons in...
Chronic Obstructive Pulmonary Disease (COPD) and asthma each represent a large proportion of the glo...
BACKGROUND: The November 2010 Joint Commission Sentinel Event Alert on the prevention of suicides in...
OBJECTIVE: Many scattered resources of knowledge are available to use for chemical accident preventi...
In Japan, the population is expected to decrease. Moreover, the proportion of elderly people living ...
The term 'quorum sensing' describes intercellular bacterial communication which regulates bacterial ...
As predicted by fuzzy-trace theory, people with a range of training—from untrained adolescents to ex...
Falling is a serious problem in an aged society such that assessment of the risk of falls for indivi...