AI Medical Compendium Journal:
Neuropathology and applied neurobiology

Showing 1 to 8 of 8 articles

Image-based deep learning reveals the responses of human motor neurons to stress and VCP-related ALS.

Neuropathology and applied neurobiology
AIMS: Although morphological attributes of cells and their substructures are recognised readouts of physiological or pathophysiological states, these have been relatively understudied in amyotrophic lateral sclerosis (ALS) research.

Deep learning-based model for diagnosing Alzheimer's disease and tauopathies.

Neuropathology and applied neurobiology
AIMS: This study aimed to develop a deep learning-based model for differentiating tauopathies, including Alzheimer's disease (AD), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD) and Pick's disease (PiD), based on tau-immunostai...

Machine learning-based decision tree classifier for the diagnosis of progressive supranuclear palsy and corticobasal degeneration.

Neuropathology and applied neurobiology
AIMS: This study aimed to clarify the different topographical distribution of tau pathology between progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) and establish a machine learning-based decision tree classifier.

Invited Review: DNA methylation-based classification of paediatric brain tumours.

Neuropathology and applied neurobiology
DNA methylation-based machine learning algorithms represent powerful diagnostic tools that are currently emerging for several fields of tumour classification. For various reasons, paediatric brain tumours have been the main driving forces behind this...

Refining Muscle Morphometry Through Machine Learning and Spatial Analysis.

Neuropathology and applied neurobiology
AIMS: Muscle morphology provides important information in differentiating disease aetiology, but its measurement remains challenging because of the lack of an efficient and objective method. This study aimed to quantitatively refine the morphological...

Evaluating the efficacy of few-shot learning for GPT-4Vision in neurodegenerative disease histopathology: A comparative analysis with convolutional neural network model.

Neuropathology and applied neurobiology
AIMS: Recent advances in artificial intelligence, particularly with large language models like GPT-4Vision (GPT-4V)-a derivative feature of ChatGPT-have expanded the potential for medical image interpretation. This study evaluates the accuracy of GPT...

Artificial intelligence in histopathological image analysis of central nervous system tumours: A systematic review.

Neuropathology and applied neurobiology
The convergence of digital pathology and artificial intelligence could assist histopathology image analysis by providing tools for rapid, automated morphological analysis. This systematic review explores the use of artificial intelligence for histopa...

Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights.

Neuropathology and applied neurobiology
AIM: Analysis of cerebrospinal fluid (CSF) is essential for diagnostic workup of patients with neurological diseases and includes differential cell typing. The current gold standard is based on microscopic examination by specialised technicians and n...