Artificial cells, nanomedicine, and biotechnology
Dec 1, 2021
BACKGROUND: Machine learning (ML) algorithms have been widely used in the classification of white blood cells (WBCs). However, the performance of ML algorithms still needs to be addressed for being short of gold standard data sets, and even the imple...
BACKGROUND AND OBJECTIVES: Emergency department (ED) overcrowding is a national crisis in which pediatric patients are often prioritized at lower levels. Because the prediction of prognosis for pediatric patients is important but difficult, we develo...
OBJECTIVES: Medical errors are the manifestation of the defects occurring in medical processes. Extracting and identifying defects as medical error factors from these processes are an effective approach to prevent medical errors. However, it is a dif...
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Nov 30, 2021
A software platform for AI-ECG algorithm research is designed and implemented to better serve the research of ECG artificial intelligence classification algorithm and to solve the problem of subjects data information management. Matlab R2019b and MyS...
Frontiers in bioscience (Landmark edition)
Nov 30, 2021
Artificial intelligence (AI) is an iterative process by which information is captured, transformed into knowledge and processed to produce adaptive changes in the environment. AI is a broad concept, involving virtual (computing) and physical (robotic...
Journal of the American Medical Informatics Association : JAMIA
Nov 25, 2021
The aim of this article was to describe a novel methodology for transforming complex nursing care plan data into meaningful variables to assess the impact of nursing care. We extracted standardized care plan data for older adults from the electronic ...
MOTIVATION: Traditional regression models are limited in outcome prediction due to their parametric nature. Current deep learning methods allow for various effects and interactions and have shown improved performance, but they typically need to be tr...
Advances in machine learning, computer vision and artificial intelligence methods, in combination with those in processing and cloud computing capability, portend the advent of true decision support during interventions in real-time and soon perhaps ...
A fundamental challenge at the interface of machine learning and neuroscience is to uncover computational principles that are shared between artificial and biological neural networks. In deep learning, normalization methods such as batch normalizatio...
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