Computational and mathematical methods in medicine
Apr 7, 2020
The detection of recorded epileptic seizure activity in electroencephalogram (EEG) segments is crucial for the classification of seizures. Manual recognition is a time-consuming and laborious process that places a heavy burden on neurologists, and he...
Predicting immunogenicity for biotherapies using patient and drug-related factors represents nowadays a challenging issue. With the growing ability to collect massive amount of data, machine learning algorithms can provide efficient predictive tools....
The Internet has been identified in human enhancement scholarship as a powerful cognitive enhancement technology. It offers instant access to almost any type of information, along with the ability to share that information with others. The aim of thi...
Neural networks : the official journal of the International Neural Network Society
Apr 6, 2020
We give a tight upper bound on the generalization error of 2-times continuously differentiable feedforward neural networks if the loss function is 2-times continuously differentiable as well. The upper bound consists of two terms, the first term indi...
The aging process results in multiple traceable footprints, which can be quantified and used to estimate an organism's age. Examples of such aging biomarkers include epigenetic changes, telomere attrition, and alterations in gene expression and metab...
A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a non-linear, machine learning algorithm (random forest) to predict minute level EE for a range of act...
Radiomics is an emerging field that involves extraction and quantification of features from medical images. These data can be mined through computational analysis and models to identify predictive image biomarkers that characterize intra-tumoral dyna...
Quasi-stable electrical fields in the EEG, called microstates carry information on the dynamics of large scale brain networks. Using machine learning techniques, we explored whether abnormalities in microstates can be used to classify patients with s...
The international journal of medical robotics + computer assisted surgery : MRCAS
Apr 6, 2020
BACKGROUND: The da Vinci Surgical System (Intuitive Surgical, Sunnyvale, CA) was introduced to overcome the limitations of single-incision laparoscopic surgery, which is challenging due to its restrictions regarding triangulation and retraction. The ...
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