AIMC Topic: Brain

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Neural networks of different species, brain areas and states can be characterized by the probability polling state.

The European journal of neuroscience
Cortical networks are complex systems of a great many interconnected neurons that operate from collective dynamical states. To understand how cortical neural networks function, it is important to identify their common dynamical operating states from ...

Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap.

Scientific reports
The analysis of neurotransmitters in the brain helps to understand brain functions and diagnose Parkinson's disease. Pharmacological inhibition experiments, electrophysiological measurement of action potentials, and mass analysers have been applied f...

Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression.

Aging
Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathoge...

Identifying Fatal Head Injuries on Postmortem Computed Tomography Using Convolutional Neural Network/Deep Learning: A Feasibility Study.

Journal of forensic sciences
Postmortem computed tomography (PMCT) is a relatively recent advancement in forensic pathology practice that has been increasingly used as an ancillary investigation and screening tool. One area of clinical CT imaging that has garnered a lot of resea...

Artificial intelligence to predict clinical disability in patients with multiple sclerosis using FLAIR MRI.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to create an algorithm that combines multiple machine-learning techniques to predict the expanded disability status scale (EDSS) score of patients with multiple sclerosis at two years solely based on age, sex an...

Classification of cognitive reserve in healthy older adults based on brain activity using support vector machine.

Physiological measurement
OBJECTIVE: Cognitive reserve (CR) refers to the capacity of the brain to actively cope with damage via the implementation of remedial cognitive processes. Traditional CR measurements focus on static proxies, which may not be able to appropriately est...

Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders.

Scientific reports
Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant scales. Several corresponding studies are now available. However, to compile a comprehensive pi...

Weakly supervised object detection with 2D and 3D regression neural networks.

Medical image analysis
Finding automatically multiple lesions in large images is a common problem in medical image analysis. Solving this problem can be challenging if, during optimization, the automated method cannot access information about the location of the lesions no...

Automated histologic diagnosis of CNS tumors with machine learning.

CNS oncology
The discovery of a new mass involving the brain or spine typically prompts referral to a neurosurgeon to consider biopsy or surgical resection. Intraoperative decision-making depends significantly on the histologic diagnosis, which is often establish...

Estimation and validation of individualized dynamic brain models with resting state fMRI.

NeuroImage
A key challenge for neuroscience is to develop generative, causal models of the human nervous system in an individualized, data-driven manner. Previous initiatives have either constructed biologically-plausible models that are not constrained by indi...