AI Medical Compendium Topic:
Alzheimer Disease

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Relational-Regularized Discriminative Sparse Learning for Alzheimer's Disease Diagnosis.

IEEE transactions on cybernetics
Accurate identification and understanding informative feature is important for early Alzheimer's disease (AD) prognosis and diagnosis. In this paper, we propose a novel discriminative sparse learning method with relational regularization to jointly p...

Predicting probable Alzheimer's disease using linguistic deficits and biomarkers.

BMC bioinformatics
BACKGROUND: The manual diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological e...

Rey's Auditory Verbal Learning Test scores can be predicted from whole brain MRI in Alzheimer's disease.

NeuroImage. Clinical
Rey's Auditory Verbal Learning Test (RAVLT) is a powerful neuropsychological tool for testing episodic memory, which is widely used for the cognitive assessment in dementia and pre-dementia conditions. Several studies have shown that an impairment in...

Application of Machine Learning in Postural Control Kinematics for the Diagnosis of Alzheimer's Disease.

Computational intelligence and neuroscience
The use of wearable devices to study gait and postural control is a growing field on neurodegenerative disorders such as Alzheimer's disease (AD). In this paper, we investigate if machine-learning classifiers offer the discriminative power for the di...

Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry.

NeuroImage. Clinical
This paper presents a brain T1-weighted structural magnetic resonance imaging (MRI) biomarker that combines several individual MRI biomarkers (cortical thickness measurements, volumetric measurements, hippocampal shape, and hippocampal texture). The ...

An algorithm for direct causal learning of influences on patient outcomes.

Artificial intelligence in medicine
OBJECTIVE: This study aims at developing and introducing a new algorithm, called direct causal learner (DCL), for learning the direct causal influences of a single target. We applied it to both simulated and real clinical and genome wide association ...

Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes.

BMC genomics
BACKGROUND: Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheim...

Early Diagnosis of Alzheimer's Disease by Joint Feature Selection and Classification on Temporally Structured Support Vector Machine.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
The diagnosis of Alzheimer's disease (AD) from neuroimaging data at the pre-clinical stage has been intensively investigated because of the immense social and economic cost. In the past decade, computational approaches on longitudinal image sequences...

Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data, with each view correspondi...

Robots to assist daily activities: views of older adults with Alzheimer's disease and their caregivers.

International psychogeriatrics
BACKGROUND: Robots have the potential to both enable older adults with dementia to perform daily activities with greater independence, and provide support to caregivers. This study explored perspectives of older adults with Alzheimer's disease (AD) a...