AIMC Topic: Brain

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The BONSAI (Brain and Optic Nerve Study with Artificial Intelligence) deep learning system can accurately identify pediatric papilledema on standard ocular fundus photographs.

Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus
BACKGROUND: Pediatric papilledema often reflects an underlying severe neurologic disorder and may be difficult to appreciate, especially in young children. Ocular fundus photographs are easy to obtain even in young children and in nonophthalmology se...

Strategies for deep learning-based attenuation and scatter correction of brain F-FDG PET images in the image domain.

Medical physics
BACKGROUND: Attenuation and scatter correction is crucial for quantitative positron emission tomography (PET) imaging. Direct attenuation correction (AC) in the image domain using deep learning approaches has been recently proposed for combined PET/M...

Application of Hybrid DeepLearning Architectures for Identification of Individuals with Obsessive Compulsive Disorder Based on EEG Data.

Clinical EEG and neuroscience
Obsessive-compulsive disorder (OCD) is a highly common psychiatric disorder. The symptoms of this condition overlap and co-occur with those of other psychiatric illnesses, making diagnosis difficult. The availability of biomarkers could be useful fo...

Determination of Alzheimer's disease based on morphology and atrophy using machine learning combined with automated segmentation.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: To evaluate the degree of cerebral atrophy for Alzheimer's disease (AD), voxel-based morphometry has been performed with magnetic resonance imaging. Detailed morphological changes in a specific tissue area having the most evidence of atro...

Active inference as a theory of sentient behavior.

Biological psychology
This review paper offers an overview of the history and future of active inference-a unifying perspective on action and perception. Active inference is based upon the idea that sentient behavior depends upon our brains' implicit use of internal model...

Memristor-Based Neuromorphic Chips.

Advanced materials (Deerfield Beach, Fla.)
In the era of information, characterized by an exponential growth in data volume and an escalating level of data abstraction, there has been a substantial focus on brain-like chips, which are known for their robust processing power and energy-efficie...

Data-driven coordinated attention deep learning for high-fidelity brain imaging denoising and inpainting.

Journal of biophotonics
Deep learning offers promise in enhancing low-quality images by addressing weak fluorescence signals, especially in deep in vivo mouse brain imaging. However, current methods struggle with photon scarcity and noise within in vivo deep mouse brains, a...

Evaluating the clinical utility of artificial intelligence assistance and its explanation on the glioma grading task.

Artificial intelligence in medicine
Clinical evaluation evidence and model explainability are key gatekeepers to ensure the safe, accountable, and effective use of artificial intelligence (AI) in clinical settings. We conducted a clinical user-centered evaluation with 35 neurosurgeons ...

A robust deep learning detector for sleep spindles and K-complexes: towards population norms.

Scientific reports
Sleep spindles (SSs) and K-complexes (KCs) are brain patterns involved in cognitive functions that appear during sleep. Large-scale sleep studies would benefit from precise and robust automatic sleep event detectors, capable of adapting the variabili...

Neural networks from biological to artificial and vice versa.

Bio Systems
In this paper, we examine how deep learning can be utilized to investigate neural health and the difficulties in interpreting neurological analyses within algorithmic models. The key contribution of this paper is the investigation of the impact of a ...