AIMC Topic: Alzheimer Disease
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Predicting long-term progression of Alzheimer's disease using a multimodal deep learning model incorporating interaction effects.
Journal of translational medicine
Mar 11, 2024
BACKGROUND: Identifying individuals with mild cognitive impairment (MCI) at risk of progressing to Alzheimer's disease (AD) provides a unique opportunity for early interventions. Therefore, accurate and long-term prediction of the conversion from MCI...
Identifying Protein Phosphorylation Site-Disease Associations Based on Multi-Similarity Fusion and Negative Sample Selection by Convolutional Neural Network.
Interdisciplinary sciences, computational life sciences
Mar 8, 2024
As one of the most important post-translational modifications (PTMs), protein phosphorylation plays a key role in a variety of biological processes. Many studies have shown that protein phosphorylation is associated with various human diseases. There...
Deep Learning-Driven Exploration of Pyrroloquinoline Quinone Neuroprotective Activity in Alzheimer's Disease.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 7, 2024
Alzheimer's disease (AD) is a pressing concern in neurodegenerative research. To address the challenges in AD drug development, especially those targeting Aβ, this study uses deep learning and a pharmacological approach to elucidate the potential of ...
miRNAs in cerebrospinal fluid associated with Alzheimer's disease: A systematic review and pathway analysis using a data mining and machine learning approach.
Journal of neurochemistry
Feb 23, 2024
Alzheimer's disease (AD) is the most common type and accounts for 60%-70% of the reported cases of dementia. MicroRNAs (miRNAs) are small non-coding RNAs that play a crucial role in gene expression regulation. Although the diagnosis of AD is primaril...
A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer's disease.
Translational psychiatry
Feb 21, 2024
Alzheimer's disease is one of the most important health-care challenges in the world. For decades, numerous efforts have been made to develop therapeutics for Alzheimer's disease, but most clinical trials have failed to show significant treatment eff...
Predictive deep learning models for cognitive risk using accessible data.
Bioscience trends
Feb 20, 2024
The early detection of mild cognitive impairment (MCI) is crucial to preventing the progression of dementia. However, it necessitates that patients voluntarily undergo cognitive function tests, which may be too late if symptoms are only recognized on...
Ranking and filtering of neuropathology features in the machine learning evaluation of dementia studies.
Brain pathology (Zurich, Switzerland)
Feb 19, 2024
Early diagnosis of dementia diseases, such as Alzheimer's disease, is difficult because of the time and resources needed to perform neuropsychological and pathological assessments. Given the increasing use of machine learning methods to evaluate neur...
Retinal imaging and Alzheimer's disease: a future powered by Artificial Intelligence.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Feb 15, 2024
Alzheimer's disease (AD) is a neurodegenerative condition that primarily affects brain tissue. Because the retina and brain share the same embryonic origin, visual deficits have been reported in AD patients. Artificial Intelligence (AI) has recently ...
Surface-functionalized SERS platform for deep learning-assisted diagnosis of Alzheimer's disease.
Biosensors & bioelectronics
Feb 12, 2024
Early diagnosis of Alzheimer's disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Rama...
Artificial intelligence for drug discovery and development in Alzheimer's disease.
Current opinion in structural biology
Feb 8, 2024
The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the development of effective therapeutics or prevention strategies. Artificial Intelligence (AI)-guided drug discovery combined with genetics/multi-omics (genomics...
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