AIMC Topic: Brain

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Unsupervised abnormality detection in neonatal MRI brain scans using deep learning.

Scientific reports
Analysis of 3D medical imaging data has been a large topic of focus in the area of Machine Learning/Artificial Intelligence, though little work has been done in algorithmic (particularly unsupervised) analysis of neonatal brain MRI's. A myriad of con...

Multidirectional Associative Memory Neural Network Circuit Based on Memristor.

IEEE transactions on biomedical circuits and systems
Multidirectional associative memory neural network(MAMNN) is a direct extension of bidirectional associative memory neural network, which can handle multiple associations. In this work, a circuit of MAMNN based on memristor is proposed, which simulat...

Human-robot collaborative task planning using anticipatory brain responses.

PloS one
Human-robot interaction (HRI) describes scenarios in which both human and robot work as partners, sharing the same environment or complementing each other on a joint task. HRI is characterized by the need for high adaptability and flexibility of robo...

Intermediately synchronised brain states optimise trade-off between subject specificity and predictive capacity.

Communications biology
Functional connectivity (FC) refers to the statistical dependencies between activity of distinct brain areas. To study temporal fluctuations in FC within the duration of a functional magnetic resonance imaging (fMRI) scanning session, researchers hav...

Heart-Brain 346-7 Score: the development and validation of a simple mortality prediction score for carbon monoxide poisoning utilizing deep learning.

Clinical toxicology (Philadelphia, Pa.)
INTRODUCTION: Acute mortality from carbon monoxide poisoning is 1-3%. The long-term mortality risk of survivors of carbon monoxide poisoning is doubled compared to age-matched controls. Cardiac involvement also increases mortality risk. We built a cl...

Perturbing BEAMs: EEG adversarial attack to deep learning models for epilepsy diagnosing.

BMC medical informatics and decision making
Deep learning models have been widely used in electroencephalogram (EEG) analysis and obtained excellent performance. But the adversarial attack and defense for them should be thoroughly studied before putting them into safety-sensitive use. This wor...

Brain imaging signatures of neuropathic facial pain derived by artificial intelligence.

Scientific reports
Advances in neuroimaging have permitted the non-invasive examination of the human brain in pain. However, a persisting challenge is in the objective differentiation of neuropathic facial pain subtypes, as diagnosis is based on patients' symptom descr...

Characteristic analysis of epileptic brain network based on attention mechanism.

Scientific reports
Constructing an efficient and accurate epilepsy detection system is an urgent research task. In this paper, we developed an EEG-based multi-frequency multilayer brain network (MMBN) and an attentional mechanism based convolutional neural network (AM-...