AIMC Topic: Brain
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Age group classification based on optical measurement of brain pulsation using machine learning.
Scientific reports
Jan 25, 2025
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monito...
The intelligent brain and the energy heart: Synergistic evolution of artificial intelligence and energy storage technology in China.
Acta psychologica
Jan 23, 2025
In the context of China's ongoing industrial revolution and technological transformation, there is a growing demand for advanced energy management solutions and the increasing role of artificial intelligence in various industries. This paper aims to ...
A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography.
NeuroImage
Jan 23, 2025
Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are pr...
Mapping the topography of spatial gene expression with interpretable deep learning.
Nature methods
Jan 23, 2025
Spatially resolved transcriptomics technologies provide high-throughput measurements of gene expression in a tissue slice, but the sparsity of these data complicates analysis of spatial gene expression patterns. We address this issue by deriving a to...
The 'Sandwich' meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding.
Journal of neural engineering
Jan 23, 2025
. Machine learning has enhanced the performance of decoding signals indicating human behaviour. Electroencephalography (EEG) brainwave decoding, as an exemplar indicating neural activity and human thoughts non-invasively, has been helpful in neural a...
A novel hybrid ViT-LSTM model with explainable AI for brain stroke detection and classification in CT images: A case study of Rajshahi region.
Computers in biology and medicine
Jan 22, 2025
Computed tomography (CT) scans play a key role in the diagnosis of stroke, a leading cause of morbidity and mortality worldwide. However, interpreting these scans is often challenging, necessitating automated solutions for timely and accurate diagnos...
Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach.
Brain topography
Jan 22, 2025
Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke. Thus, the aim of the study was to identify biomarkers to discriminate stroke patients from healthy individuals based on EEG-MS and clinical features...
A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity.
Scientific reports
Jan 22, 2025
Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality of predictive models trained on functional connectomes, combined with small sample sizes in clinical research, increases the risk of overfitting. Rece...
Investigating the intrinsic top-down dynamics of deep generative models.
Scientific reports
Jan 22, 2025
Hierarchical generative models can produce data samples based on the statistical structure of their training distribution. This capability can be linked to current theories in computational neuroscience, which propose that spontaneous brain activity ...
Development of compositionality through interactive learning of language and action of robots.
Science robotics
Jan 22, 2025
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental que...
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