AIMC Topic: Time Factors

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Predicting mechanical restraint of psychiatric inpatients by applying machine learning on electronic health data.

Acta psychiatrica Scandinavica
OBJECTIVE: Mechanical restraint (MR) is used to prevent patients from harming themselves or others during inpatient treatment. The objective of this study was to investigate whether incident MR occurring in the first 3 days following admission could ...

Body Patches in Inferior Temporal Cortex Encode Categories with Different Temporal Dynamics.

Journal of cognitive neuroscience
An unresolved question in cognitive neuroscience is how representations of object categories at different levels (basic and superordinate) develop during the course of the neural response within an area. To address this, we decoded categories of diff...

[Renal graft survival in patients transplanted from organs of deceased donors].

Revista medica del Instituto Mexicano del Seguro Social
BACKGROUND: In Mexico, out of the total number of transplants it was reported, in 2014, a frequency of 29% of deceased donor renal transplantation (DDRT). The use of kidneys from deceased elderly donors is increasing over the years. Currently, some a...

Linguistic summarization of in-home sensor data.

Journal of biomedical informatics
INTRODUCTION: With the increase in the population of older adults around the world, a significant amount of work has been done on in-home sensor technology to aid the elderly age independently. However, due to the large amounts of data generated by t...

Using machine learning to characterize heart failure across the scales.

Biomechanics and modeling in mechanobiology
Heart failure is a progressive chronic condition in which the heart undergoes detrimental changes in structure and function across multiple scales in time and space. Multiscale models of cardiac growth can provide a patient-specific window into the p...

A diversity of interneurons and Hebbian plasticity facilitate rapid compressible learning in the hippocampus.

Nature neuroscience
The hippocampus is able to rapidly learn incoming information, even if that information is only observed once. Furthermore, this information can be replayed in a compressed format in either forward or reverse modes during sharp wave-ripples (SPW-Rs)....

Quasi-projective and complete synchronization of fractional-order complex-valued neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
This paper studies quasi-projective synchronization (QPS) and complete synchronization (CS) for a class of fractional-order complex-valued neural networks with time delays by designing suitable controllers. To realize QPS and CS, linear feedback cont...

Short-term synaptic plasticity expands the operational range of long-term synaptic changes in neural networks.

Neural networks : the official journal of the International Neural Network Society
The brain is highly plastic, with synaptic weights changing across a wide range of time scales, from hundreds of milliseconds to days. Changes occurring at different temporal scales are believed to serve different purposes, with long-term changes for...