Geriatrics

A machine learning-based linguistic battery for diagnosing mild cognitive impairment due to Alzheimer's disease.

There is a limited evaluation of an independent linguistic battery for early diagnosis of Mild Cognitive Impairment due to Alzheimer's disease (MCI-AD). We hypothesized that an independent linguistic battery comprising of only the language components or subtests of popular test batteries could give a better clinical diagnosis for MCI-AD compared to using an exhaustive battery of tests. As such, we...

Factors that affect younger and older adults' causal attributions of robot behaviour.

Stereotypes are cognitive shortcuts that facilitate efficient social judgments about others. Just as causal attributions affect perceptions of people, they may similarly affect perceptions of technology, particularly anthropomorphic technology such as robots. In a scenario-based study, younger and older adults judged the performance and capability of an anthropomorphised robot that appeared young ...

Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications.

The identification of drug-drug interactions (DDIs) is important for patient safety; yet, compared to other pharmacovigilance work, a limited amount o...

Identification of elders at higher risk for fall with statewide electronic health records and a machine learning algorithm.

OBJECTIVE: Predicting the risk of falls in advance can benefit the quality of care and potentially reduce mortality and morbidity in the older populat...

The Effect of Using PARO for People Living With Dementia and Chronic Pain: A Pilot Randomized Controlled Trial.

OBJECTIVES: To evaluate the effect of interaction with a robotic seal (PARO) on pain and behavioral and psychological symptoms of people with dementia...

A novel CNN based Alzheimer's disease classification using hybrid enhanced ICA segmented gray matter of MRI.

Predicting Alzheimer's Disease (AD) from Mild Cognitive Impairment (MCI) and Cognitive Normal (CN) has become wide. Recent advancement in neuroimaging...

A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder.

BACKGROUND: Concomitant use of complementary, multimodal imaging measures and neurocognitive measures is reported to have higher accuracy as a biomark...

A combination of 3-D discrete wavelet transform and 3-D local binary pattern for classification of mild cognitive impairment.

BACKGROUND: The detection of Alzheimer's Disease (AD) in its formative stages, especially in Mild Cognitive Impairments (MCI), has the potential of he...

Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.

OBJECTIVE: Osteoporosis is a prevalent and treatable condition, but it remains underdiagnosed. In this study, a deep learning-based system was develop...

Measuring the impact of age, gender and dementia on communication-robot interventions in residential care homes.

AIM: The primary aim of this study was to examine the impact of age, gender and the stage of dementia on the results of an assistive technology interv...

Space-independent community and hub structure of functional brain networks.

Coordinated brain activity reflects underlying cognitive processes and can be modeled as a network of inter-regional functional connections. The most ...

A comparison between Artificial Neural Network and Hybrid Intelligent Genetic Algorithm in predicting the severity of fixed object crashes among elderly drivers.

Run-off-road (ROR) crashes have always been a major concern as this type of crash is usually associated with a considerable number of serious injury a...

An End-to-End Multi-Task Deep Learning Framework for Skin Lesion Analysis.

Automatic skin lesion analysis of dermoscopy images remains a challenging topic. In this paper, we propose an end-to-end multi-task deep learning fram...

Multimodal Data Analysis of Alzheimer's Disease Based on Clustering Evolutionary Random Forest.

Alzheimer's disease (AD) has become a severe medical challenge. Advances in technologies produced high-dimensional data of different modalities includ...

On the localness modeling for the self-attention based end-to-end speech synthesis.

Attention based end-to-end speech synthesis achieves better performance in both prosody and quality compared to the conventional "front-end"-"back-end...

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning.

INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a c...

Towards an ontology of cognitive processes and their neural substrates: A structural equation modeling approach.

A key challenge in the field of cognitive neuroscience is to identify discriminable cognitive functions, and then map these functions to brain activit...

A review of recent research in social robotics.

Research in social robotics has a different emphasis from research in robotics for factory, military, hospital, home (vacuuming), aerial (drone), spac...

Reconstruction of natural visual scenes from neural spikes with deep neural networks.

Neural coding is one of the central questions in systems neuroscience for understanding how the brain processes stimulus from the environment, moreove...

Deep Learning Prediction of Mild Cognitive Impairment using Electronic Health Records.

About 44.4 million people have been diagnosed with dementia worldwide, and it is estimated that this number will be almost tripled by 2050. Predicting...