AIMC Topic: Brain

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Brain Tumor Detection Using Machine Learning and Deep Learning: A Review.

Current medical imaging
According to the International Agency for Research on Cancer (IARC), the mortality rate due to brain tumors is 76%. It is required to detect the brain tumors as early as possible and to provide the patient with the required treatment to avoid any fat...

Automated Assessment of Brain CT After Cardiac Arrest-An Observational Derivation/Validation Cohort Study.

Critical care medicine
OBJECTIVES: Prognostication of outcome is an essential step in defining therapeutic goals after cardiac arrest. Gray-white-matter ratio obtained from brain CT can predict poor outcome. However, manual placement of regions of interest is a potential s...

Shedding light on pain for the clinic: a comprehensive review of using functional near-infrared spectroscopy to monitor its process in the brain.

Pain
Pain is a complex experience that involves sensation, emotion, and cognition. The subjectivity of the traditional pain measurement tools has expedited the interest in developing neuroimaging techniques to monitor pain objectively. Among noninvasive n...

A Correspondence Between Normalization Strategies in Artificial and Biological Neural Networks.

Neural computation
A fundamental challenge at the interface of machine learning and neuroscience is to uncover computational principles that are shared between artificial and biological neural networks. In deep learning, normalization methods such as batch normalizatio...

The neural architecture of language: Integrative modeling converges on predictive processing.

Proceedings of the National Academy of Sciences of the United States of America
The neuroscience of perception has recently been revolutionized with an integrative modeling approach in which computation, brain function, and behavior are linked across many datasets and many computational models. By revealing trends across models,...

Yulong Li.

Neuron
In an interview with Neuron, Yulong Li discusses optical tool development and next steps to interrogate the whole brain. He further shares the importance of interdisciplinarity; how new tools for neural imaging, perturbation, and artificial intellige...

Instantaneous Brain Strain Estimation for Automotive Head Impacts via Deep Learning.

Stapp car crash journal
Efficient brain strain estimation is critical for routine application of a head injury model. Lately, a convolutional neural network (CNN) has been successfully developed to estimate spatially detailed brain strains instantly and accurately in contac...

Uncovering the effect of different brain regions on behavioral classification using recurrent neural networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
As our ability to record neural activity from a larger number of brain areas increases, we need to develop tools to understand how this activity is related to ongoing behavior. Recurrent neural networks (RNNs) have been shown to perform successful cl...

EEG-based Emotion Recognition Using Graph Convolutional Network with Learnable Electrode Relations.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Emotion recognition based on electroencephalography (EEG) plays a pivotal role in the field of affective computing, and graph convolutional neural network (GCN) has been proved to be an effective method and made considerable progress. Since the adjac...

Analysis of Human Head Motion and Robotic Compensation for PET Imaging Studies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Functional medical imaging systems can provide insights into brain activity during various tasks, but most current imaging systems are bulky devices that are not compatible with many human movements. Our motivating application is to perform Positron ...