AIMC Topic: Middle Aged

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Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding.

NeuroImage
White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their characteristics both at population- and subject-level, making their detection a challenging task. Population-level factors such as age, vascular risk factor...

A neural network-based software to recognise blepharospasm symptoms and to measure eye closure time.

Computers in biology and medicine
Blepharospasm (BSP) is an adult-onset focal dystonia with phenomenologically heterogeneous effects, including, but not limited to, blinks, brief or prolonged spasms, and a narrowing or closure of the eyelids. In spite of the clear and well-known symp...

Artificial neural networks reveal individual differences in metacognitive monitoring of memory.

PloS one
Previous work supports an age-specific impairment for recognition memory of pairs of words and other stimuli. The present study tested the generalization of an associative deficit across word, name, and nonword stimulus types in younger and older adu...

Combining patient visual timelines with deep learning to predict mortality.

PloS one
BACKGROUND: Deep learning algorithms have achieved human-equivalent performance in image recognition. However, the majority of clinical data within electronic health records is inherently in a non-image format. Therefore, creating visual representati...

Performance of deep learning for differentiating pancreatic diseases on contrast-enhanced magnetic resonance imaging: A preliminary study.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to evaluate the ability of deep learning to differentiate pancreatic diseases on contrast-enhanced magnetic resonance (MR) images with the aid of generative adversarial network (GAN).

Epileptic Seizure Detection with EEG Textural Features and Imbalanced Classification Based on EasyEnsemble Learning.

International journal of neural systems
Imbalance data classification is a challenging task in automatic seizure detection from electroencephalogram (EEG) recordings when the durations of non-seizure periods are much longer than those of seizure activities. An imbalanced learning model is ...

[Machine learning for predictive analyses in health: an example of an application to predict death in the elderly in São Paulo, Brazil].

Cadernos de saude publica
This study aims to present the stages related to the use of machine learning algorithms for predictive analyses in health. An application was performed in a database of elderly residents in the city of São Paulo, Brazil, who participated in the Healt...

Generalizability of A Neural Network Model for Circadian Phase Prediction in Real-World Conditions.

Scientific reports
A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals on a fixed sleep schedule. This study aimed to test the generalizability of the model to other slee...

A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk.

Breast cancer research : BCR
BACKGROUND: Breast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected breast cancers. The overall risk for DCIS patients treated with breast-conserving surgery stems almost exclusively from local recurrence. Although a mas...

Robot-assisted gait training for balance and lower extremity function in patients with infratentorial stroke: a single-blinded randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: Balance impairments are common in patients with infratentorial stroke. Although robot-assisted gait training (RAGT) exerts positive effects on balance among patients with stroke, it remains unclear whether such training is superior to con...