AIMC Topic: Neurodegenerative Diseases

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Artificial intelligence in gut microbiome research: Toward predictive diagnostics for neurodegenerative disorders.

Acta microbiologica et immunologica Hungarica
The human gut microbiota plays a pivotal role in maintaining host immunity, regulating metabolism, and sustaining neurophysiological homeostasis. Increasing evidence implicates gut dysbiosis in the onset and progression of neurodegenerative disorders...

K-operator for Modelling Neurodegeneration: Simulations, fMRI Application, Eigenvalue Analysis and Recurrence Plots.

Journal of medical systems
The brain network damage provoked by a neurological disease can be modelled as the result of the action of an operator, K, acting on the brain, inspired by physics. Here, we explore the matrix formulation of K, analysing eigenvalues and eigenvectors,...

Deep Learning in neuroimaging for neurodegenerative diseases: State-of-the art, Challenges, and Opportunities.

Journal of the neurological sciences
Neuroimaging is commonly used to diagnose neurodegenerative diseases (NDDs), providing crucial insights into brain changes before clinical symptoms manifest. Deep learning (DL) for neuroimaging can improve early diagnosis and disease monitoring. Clin...

Biomaterials for CNS disorders: a review of development from traditional methods to AI-assisted optimization.

Journal of materials science. Materials in medicine
Treating neurodegenerative and traumatic brain disorders is profoundly challenging due to factors like permanent tissue loss and the restrictive nature of the Blood-Brain Barrier (BBB), which limits drug delivery to the brain. Biomaterials offer a pr...

Rehabilitation, neuroplasticity, and machine learning: Approaching artificial intelligence for equitable health systems.

Neuroscience
Recently, technology has evolved significantly in the rehabilitation process for neurological disorders and neurodegenerative diseases, focusing on neuroplasticity. Neuroplasticity, as a fundamental base of brain rehabilitation, is the change in the ...

VacQuant: a tool to quantify neurodegeneration and associated vacuolation in brain tissue.

Fly
Neurodegenerative diseases are devastating conditions characterized by progressive cognitive decline with few available treatments. Neurodegeneration can be quantified in vertebrate and invertebrate models of disease by analysis of vacuolation - the ...

Utility of the continuous spectrum formed by pathological states in characterizing disease properties.

NPJ systems biology and applications
Understanding diseases as the result of continuous transitions from a healthy system is more realistic than understanding them as discrete states. Here, we designed the spectrum formation approach (SFA), a machine learning-based method that extracts ...

Advancements in the investigation of the mechanisms underlying cognitive aging.

Biogerontology
Cognitive aging, a pivotal domain at the intersection of neuroscience and psychology, exhibits a strong association with neurodegenerative disorders; however, its comprehensive underlying mechanisms remain incompletely elucidated. This review aims to...

Targeting neurodegeneration: three machine learning methods for G9a inhibitors discovery using PubChem and scikit-learn.

Journal of computer-aided molecular design
In light of the increasing interest in G9a's role in neuroscience, three machine learning (ML) models, that are time efficient and cost effective, were developed to support researchers in this area. The models are based on data provided by PubChem an...

Structural modification strategies for ferritin nanoparticles and their applications in biomedicine: a narrative review.

Nanoscale
Ferritin is an iron-storage protein that naturally self-assembles into a hollow spherical particle consisting of 24 identical subunits, and it serves a central role in iron metabolism. Ferritin's favorable drug-loading capacity, biocompatibility, int...