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Neurodegenerative Diseases

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Deep learning-based brain age prediction in normal aging and dementia.

Nature aging
Brain aging is accompanied by patterns of functional and structural change. Alzheimer's disease (AD), a representative neurodegenerative disease, has been linked to accelerated brain aging. Here, we developed a deep learning-based brain age predictio...

3-Dimensional Immunostaining and Automated Deep-Learning Based Analysis of Nerve Degeneration.

International journal of molecular sciences
Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease driven by inflammation and demyelination in the brain, spinal cord, and optic nerve. Optic neuritis, characterized by inflammation and demyelination of the optic nerve, is a sympt...

Explainable classification of Parkinson's disease using deep learning trained on a large multi-center database of T1-weighted MRI datasets.

NeuroImage. Clinical
INTRODUCTION: Parkinson's disease (PD) is a severe neurodegenerative disease that affects millions of people. Early diagnosis is important to facilitate prompt interventions to slow down disease progression. However, accurate PD diagnosis can be chal...

Multi-speed transformer network for neurodegenerative disease assessment and activity recognition.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Neurodegenerative diseases are the most frequent age-related diseases. This type of disease, if not discovered in the initial stage, will compromise the quality of life of the affected subject. Thus, a timely diagnosis is of...

Neurodegenerative disease of the brain: a survey of interdisciplinary approaches.

Journal of the Royal Society, Interface
Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective therapies over the last decade. Interdisciplinary research is improving understanding of these diseas...

Restoring arm function with a soft robotic wearable for individuals with amyotrophic lateral sclerosis.

Science translational medicine
Despite promising results in the rehabilitation field, it remains unclear whether upper limb robotic wearables, e.g., for people with physical impairments resulting from neurodegenerative disease, can be made portable and suitable for everyday use. W...

Diagnosis of Alzheimer Disease and Tauopathies on Whole-Slide Histopathology Images Using a Weakly Supervised Deep Learning Algorithm.

Laboratory investigation; a journal of technical methods and pathology
Neuropathologic assessment during autopsy is the gold standard for diagnosing neurodegenerative disorders. Neurodegenerative conditions, such as Alzheimer disease (AD) neuropathological change, are a continuous process from normal aging rather than c...

Bifunctional robots inducing targeted protein degradation.

European journal of medicinal chemistry
The gaining importance of Targeted Protein Degradation (TPD) and PROTACs (PROteolysis-TArgeting Chimeras) have drawn the scientific community's attention. PROTACs are considered bifunctional robots owing to their avidity for the protein of interest (...

Diagnosis of Parkinson's Disease via the Metabolic Fingerprint in Saliva by Deep Learning.

Small methods
Parkinson's disease (PD) is the second cause of the neurodegenerative disorder, affecting over 6 million people worldwide. The World Health Organization estimated that population aging will cause global PD prevalence to double in the coming 30 years....

msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping.

NeuroImage
Quantitative susceptibility mapping (QSM) has been applied to the measurement of iron deposition and the auxiliary diagnosis of neurodegenerative disease. There still exists a dipole inversion problem in QSM reconstruction. Recently, deep learning ap...