AIMC Topic: Time Factors

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Measuring Functional Arm Movement after Stroke Using a Single Wrist-Worn Sensor and Machine Learning.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND AND PURPOSE: Trials of restorative therapies after stroke and clinical rehabilitation require relevant and objective efficacy end points; real-world upper extremity (UE) functional use is an attractive candidate. We present a novel, inexpe...

DropConnected neural networks trained on time-frequency and inter-beat features for classifying heart sounds.

Physiological measurement
OBJECTIVE: Automatic heart sound analysis has the potential to improve the diagnosis of valvular heart diseases in the primary care phase, as well as in countries where there is neither the expertise nor the equipment to perform echocardiograms. An a...

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows.

BMC medical informatics and decision making
BACKGROUND: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patient...

Predictors of short-term and long-term incontinence after robot-assisted radical prostatectomy.

The Journal of international medical research
Purpose To determine retrospectively the prognostic factors for urinary incontinence following robot-assisted radical prostatectomy (RARP). Methods Altogether, 180 patients with localized prostate cancer underwent RARP (same surgeon). Preoperative ph...

Deep Learning based Radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma.

Scientific reports
Deep learning-based radiomics (DLR) was developed to extract deep information from multiple modalities of magnetic resonance (MR) images. The performance of DLR for predicting the mutation status of isocitrate dehydrogenase 1 (IDH1) was validated in ...

Identifying incipient dementia individuals using machine learning and amyloid imaging.

Neurobiology of aging
Identifying individuals destined to develop Alzheimer's dementia within time frames acceptable for clinical trials constitutes an important challenge to design studies to test emerging disease-modifying therapies. Although amyloid-β protein is the co...

Decomposition approach to the stability of recurrent neural networks with asynchronous time delays in quaternion field.

Neural networks : the official journal of the International Neural Network Society
In this paper, the global exponential stability for recurrent neural networks (QVNNs) with asynchronous time delays is investigated in quaternion field. Due to the non-commutativity of quaternion multiplication resulting from Hamilton rules: ij=-ji=k...

Modeling time-to-event (survival) data using classification tree analysis.

Journal of evaluation in clinical practice
RATIONALE, AIMS, AND OBJECTIVES: Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (cal...

Efficiency of rate and latency coding with respect to metabolic cost and time.

Bio Systems
Recent studies on the theoretical performance of latency and rate code in single neurons have revealed that the ultimate accuracy is affected in a nontrivial way by aspects such as the level of spontaneous activity of presynaptic neurons, amount of n...