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Convolutional Invasion and Expansion Networks for Tumor Growth Prediction.

IEEE transactions on medical imaging
Tumor growth is associated with cell invasion and mass-effect, which are traditionally formulated by mathematical models, namely reaction-diffusion equations and biomechanics. Such models can be personalized based on clinical measurements to build th...

Robotics in MRI-Guided Interventions.

Topics in magnetic resonance imaging : TMRI
Robots have been found to be a useful tool in magnetic resonance imaging (MRI)-guided intervention. The utility of robots in MRI-guided therapy ranges from aid for precision targeting to high-dexterity surgical tools to improve or even enable new MRI...

Deep neural networks are more accurate than humans at detecting sexual orientation from facial images.

Journal of personality and social psychology
We show that faces contain much more information about sexual orientation than can be perceived or interpreted by the human brain. We used deep neural networks to extract features from 35,326 facial images. These features were entered into a logistic...

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

Journal of neural engineering
OBJECTIVE: Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit h...

Impressions of Humanness for Android Robot may Represent an Endophenotype for Autism Spectrum Disorders.

Journal of autism and developmental disorders
Identification of meaningful endophenotypes may be critical to unraveling the etiology and pathophysiology of autism spectrum disorders (ASD). We investigated whether impressions of "humanness" for android robot might represent a candidate characteri...

Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment.

Journal of acquired immune deficiency syndromes (1999)
OBJECTIVE: Universal HIV screening programs are costly, labor intensive, and often fail to identify high-risk individuals. Automated risk assessment methods that leverage longitudinal electronic health records (EHRs) could catalyze targeted screening...

Validation of artificial neural networks as a methodology for donor-recipient matching for liver transplantation.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society
In 2014, we reported a model for donor-recipient (D-R) matching in liver transplantation (LT) based on artificial neural networks (ANNs) from a Spanish multicenter study (Model for Allocation of Donor and Recipient in EspaƱa [MADR-E]). The aim is to ...

Inferring imagined speech using EEG signals: a new approach using Riemannian manifold features.

Journal of neural engineering
OBJECTIVE: In this paper, we investigate the suitability of imagined speech for brain-computer interface (BCI) applications.

An automated behavioral measure of mind wandering during computerized reading.

Behavior research methods
Mind wandering is a ubiquitous phenomenon in which attention shifts from task-related to task-unrelated thoughts. The last decade has witnessed an explosion of interest in mind wandering, but research has been stymied by a lack of objective measures,...