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How adaptation, training, and customization contribute to benefits from exoskeleton assistance.

Science robotics
Exoskeletons can enhance human mobility, but we still know little about why they are effective. For example, we do not know the relative importance of training, how much is required, or what type is most effective; how people adapt with the device; o...

Cutoff criteria for the placebo response: a cluster and machine learning analysis of placebo analgesia.

Scientific reports
Computations of placebo effects are essential in randomized controlled trials (RCTs) for separating the specific effects of treatments from unspecific effects associated with the therapeutic intervention. Thus, the identification of placebo responder...

An automated liver segmentation in liver iron concentration map using fuzzy c-means clustering combined with anatomical landmark data.

BMC medical imaging
BACKGROUND: To estimate median liver iron concentration (LIC) calculated from magnetic resonance imaging, excluded vessels of the liver parenchyma region were defined manually. Previous works proposed the automated method for excluding vessels from t...

A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images.

NeuroImage
A tool was developed to automatically segment several subcortical limbic structures (nucleus accumbens, basal forebrain, septal nuclei, hypothalamus without mammillary bodies, the mammillary bodies, and fornix) using only a T1-weighted MRI as input. ...

Forecasting care seekers satisfaction with telemedicine using machine learning and structural equation modeling.

PloS one
Many individuals visit rural telemedicine centres to obtain safe and effective health remedies for their physical and emotional illnesses. This study investigates the antecedents of patients' satisfaction relating to telemedicine adoption in rural pu...

Prediction of blood supply in vestibular schwannomas using radiomics machine learning classifiers.

Scientific reports
This study attempts to explore the radiomics-based features of multi-parametric magnetic resonance imaging (MRI) and construct a machine-learning model to predict the blood supply in vestibular schwannoma preoperatively. By retrospectively collecting...

The relevance of signal timing in human-robot collaborative manipulation.

Science robotics
To achieve a seamless human-robot collaboration, it is crucial that robots express their intentions without perturbating or interrupting the task that a human partner is performing at that moment. Although it has not received much attention so far, t...

Persuasive robots should avoid authority: The effects of formal and real authority on persuasion in human-robot interaction.

Science robotics
Social robots must take on many roles when interacting with people in everyday settings, some of which may be authoritative, such as a nurse, teacher, or guard. It is important to investigate whether and how authoritative robots can influence people ...

A Machine Learning Model for Evaluating Imported Disease Screening Strategies in Immigrant Populations.

The American journal of tropical medicine and hygiene
Given the high prevalence of imported diseases in immigrant populations, it has postulated the need to establish screening programs that allow their early diagnosis and treatment. We present a mathematical model based on machine learning methodologie...

Multi-step validation of a deep learning-based system for the quantification of bowel preparation: a prospective, observational study.

The Lancet. Digital health
BACKGROUND: Inadequate bowel preparation is associated with a decrease in adenoma detection rate (ADR). A deep learning-based bowel preparation assessment system based on the Boston bowel preparation scale (BBPS) has been previously established to ca...