AIMC Topic: Female

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Dynamic network modeling and dimensionality reduction for human ECoG activity.

Journal of neural engineering
OBJECTIVE: Developing dynamic network models for multisite electrocorticogram (ECoG) activity can help study neural representations and design neurotechnologies in humans given the clinical promise of ECoG. However, dynamic network models have so far...

Age grading An. gambiae and An. arabiensis using near infrared spectra and artificial neural networks.

PloS one
BACKGROUND: Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into < or ≥ 7 days old with an average accuracy of 80%, achieved by training a re...

Exploring Skills Gained Through a Robotics Program for Youth With Disabilities.

OTJR : occupation, participation and health
Children with disabilities often have fewer opportunities to engage in science, technology, engineering, and math programs that can enhance their educational and career opportunities. This study explored the quality, experience, and skills learned in...

Can Machine Learning help us in dealing with treatment resistant depression? A review.

Journal of affective disorders
BACKGROUND: About one third of patients treated with antidepressant do not show sufficient symptoms relief and up to 15% of patients remain symptomatic even after multiple trials are applied, configuring a state called treatment resistant depression ...

Effects of a robot intervention on visuospatial hemineglect in postacute stroke patients: a randomized controlled trial.

Clinical rehabilitation
OBJECTIVE: To evaluate the effects of an intervention using the robot device PARO on visuospatial hemineglect and activities of daily living, and its acceptance during stroke rehabilitation. PARO is an interactive robotic toy with the appearance of a...

Physiological indices of challenge and threat: A data-driven investigation of autonomic nervous system reactivity during an active coping stressor task.

Psychophysiology
We utilized a data-driven, unsupervised machine learning approach to examine patterns of peripheral physiological responses during a motivated performance context across two large, independent data sets, each with multiple peripheral physiological me...

Clustering-based undersampling with random over sampling examples and support vector machine for imbalanced classification of breast cancer diagnosis.

Computer assisted surgery (Abingdon, England)
To overcome the two-class imbalanced classification problem existing in the diagnosis of breast cancer, a hybrid of Random Over Sampling Example, K-means and Support vector machine (RK-SVM) model is proposed which is based on sample selection. Random...

An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis.

Nature medicine
The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer, and thus guides therapy. However, these assessments demonstrate considerable variability and many regions of the world lack access to trained pathol...