Alzheimer's disease
PulseAugur coverage of Alzheimer's disease — every cluster mentioning Alzheimer's disease across labs, papers, and developer communities, ranked by signal.
- used by Alzheimer's Disease Neuroimaging Initiative 70%
- instance of Alzheimer's Disease Neuroimaging Initiative 70%
- used by magnetic resonance imaging 70%
- used by Tau PET Imaging in the NACC Study Cohort 70%
- instance of tadpole 70%
- used by mini–mental state examination 70%
- used by tadpole 70%
- used by Oasis 3 70%
- instance of magnetic resonance imaging 50%
16 day(s) with sentiment data
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New AI model improves Alzheimer's prediction using fMRI data
Researchers have developed a novel SDE-Driven Spatio-Temporal Hypergraph Neural Network (SDE-HGNN) to improve the modeling of Alzheimer's disease progression using longitudinal fMRI data. This framework addresses challe…
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AI digital twins model Alzheimer's protein spread with 87% accuracy
Researchers have developed a novel data-driven framework using operator learning to create patient-specific digital twins for Alzheimer's disease. This approach models the progression of amyloid-β and tau proteins by in…
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Zhonggu Logistics to sell 3 ships for over 570M yuan; Huadong Medicine drug trial approved
Zhonggu Logistics plans to sell three container ships, "Zhonggu 20", "Zhonggu 21", and "Zhonggu Chengdu", through public auction or private transfer. The estimated total sale price is no less than 570 million yuan. This…
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Huadong Medicine subsidiary gains approval for novel cancer drug clinical trial
Huadong Medicine's subsidiary, Hangzhou Sino-American Huadong Pharmaceutical, has received approval from China's National Medical Products Administration for a clinical trial of its injectable HDM2005 drug. This drug is…
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AI system ProMUSE cuts Alzheimer's diagnosis costs with adaptive imaging
Researchers have developed ProMUSE, a novel AI system designed to improve the early diagnosis of Alzheimer's disease by adaptively incorporating multi-modal data. This system initially uses low-cost clinical assessments…
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AI framework REVEAL++ improves Alzheimer's risk prediction using retinal scans
Researchers have developed REVEAL++, a novel framework for predicting Alzheimer's disease risk using retinal imaging and clinical data. This new approach employs a differentiable phenotypic grouping method, allowing for…
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New taxonomy links caregiver needs to technology for Alzheimer's and dementia care
A new taxonomy has been developed to bridge the gap between the mental health needs of Alzheimer's and dementia caregivers and the available technological solutions. This framework, derived from literature reviews and c…
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New SMART framework offers flexible, interpretable brain atlas from medical imaging
Researchers have developed SMART, a novel framework for creating flexible, interpretable, and scalable spatio-temporal brain atlases from high-resolution medical imaging data. Unlike previous black-box models, SMART dec…
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New Manifold GCN Layers Outperform State-of-the-Art on Graph Data
Researchers have developed new graph neural network layers designed for data residing on Riemannian manifolds. These layers, named Manifold GCN, are based on a diffusion equation and a tangent multilayer perceptron, off…
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New AI method harmonizes Alzheimer's PET scans, improving disease tracking
Researchers have developed a new method called Feynman Kac Reweighted Schrödinger Bridge Matching (FKRSBM) to harmonize tau PET imaging data, which is crucial for tracking Alzheimer's disease progression. Existing metho…
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Multimodal LLM advances neurodegenerative disease staging
Researchers have developed NeurMLLM, a novel multimodal large language model designed for staging neurodegenerative diseases like Alzheimer's and Parkinson's. This framework integrates acoustic features from speech, tex…
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New AI Model Synthesizes Tau PET Images from MRI for Alzheimer's Diagnosis
Researchers have developed MCR-VQGAN, a novel generative adversarial network designed to synthesize high-fidelity tau positron emission tomography (PET) images from structural MRI scans. This approach aims to overcome t…
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New AI models enhance Alzheimer's diagnosis with multimodal data analysis
Researchers have developed new methods for analyzing multimodal data to improve Alzheimer's disease diagnosis. One study uses quantitative analysis of tau-PET, MRI, and cognitive scores to understand biomarker relations…
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Deep learning model forecasts Alzheimer's progression with uncertainty estimation · 4 sources tracked
Researchers have developed a deep learning framework to forecast Alzheimer's disease progression with improved accuracy and uncertainty estimation. This probabilistic model, adapted from a Temporal Fusion Transformer, p…
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New Bayesian Network Model Tracks Alzheimer's Disease Progression
Researchers have developed a new framework called Bayesian Networks with Latent Time Embedding (BN-LTE) to model the progression of Alzheimer's disease. This approach uses Bayesian networks to estimate disease pseudotim…
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Hybrid AI pipeline classifies Alzheimer's using quantum kernels
Researchers have developed a novel Hybrid Classical-Quantum (HCQ) pipeline for classifying Alzheimer's disease (AD) using 3D structural MRI scans. The system employs a supervised 3D $\beta$-variational autoencoder (VAE)…
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New Graph Network Improves Alzheimer's Diagnosis with MRI Data
Researchers have developed GMN4AD, a novel Graph Matching Network designed for diagnosing Alzheimer's Disease using structural Magnetic Resonance Imaging (sMRI). This network addresses challenges posed by data heterogen…
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OmniBioTwin framework enhances health digital twins with modular systems
Researchers have introduced OmniBioTwin, a novel framework designed to create more integrated and comprehensive health digital twins. This system-of-twinned-systems approach organizes digital twins as modular components…
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AI model forecasts Alzheimer's progression using routine patient data
Researchers have developed a new framework called GNOVA, which uses a GRU-Neural ODE Variational Autoencoder to predict and reconstruct Alzheimer's disease progression. This model can forecast cognitive scores like CDR-…
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AI models predict Alzheimer's disease severity and progression
Researchers have developed advanced machine learning models to predict Alzheimer's disease severity and progression. One approach uses multimodal data, including MRI scans and clinical information, with an ordinal regre…