AIMC Topic: Adult

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Robotic single port cholecystectomy: current data and future perspectives.

Minerva chirurgica
INTRODUCTION: Minimally invasive techniques are used more and more frequently. Since conventional laparoscopic approach has been the gold standard, surgeons in their effort to further reduce the invasiveness of conventional laparoscopic cholecystecto...

Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?

Sensors (Basel, Switzerland)
Human movement analysis has become easier with the wide availability of motion capture systems. Inertial sensing has made it possible to capture human motion without external infrastructure, therefore allowing measurements in any environment. As high...

Effects of the Red Bull energy drink on cognitive function and mood in healthy young volunteers.

Journal of psychopharmacology (Oxford, England)
The present study compared the cognitive and mood effects of two commercially available products, Red Bull energy drink 250 mL and Red Bull Sugarfree energy drink 250 mL, together with a matching placebo 250 mL. Twenty-four healthy young volunteers t...

Natalizumab-associated progressive multifocal leukoencephalopathy is not preceded by elevated drug concentrations.

Multiple sclerosis (Houndmills, Basingstoke, England)
BACKGROUND: In recent years, a small but increasing number of neurologists choose to extend dose intervals of natalizumab with the aim of reducing the risk of progressive multifocal leukoencephalopathy (PML). This idea is based on the hypothesis that...

Metrics of brain network architecture capture the impact of disease in children with epilepsy.

NeuroImage. Clinical
BACKGROUND AND OBJECTIVE: Epilepsy is associated with alterations in the structural framework of the cerebral network. The aim of this study was to measure the potential of global metrics of network architecture derived from resting state functional ...

Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity.

Proceedings of the National Academy of Sciences of the United States of America
The effectiveness of today's human-machine interaction is limited by a communication bottleneck as operators are required to translate high-level concepts into a machine-mandated sequence of instructions. In contrast, we demonstrate effective, goal-o...

Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia.

Scientific reports
Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging ...

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.

PloS one
BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research w...

A Model-Based Machine Learning Approach to Probing Autonomic Regulation From Nonstationary Vital-Sign Time Series.

IEEE journal of biomedical and health informatics
Physiological variables, such as heart rate (HR), blood pressure (BP) and respiration (RESP), are tightly regulated and coupled under healthy conditions, and a break-down in the coupling has been associated with aging and disease. We present an appro...