Geriatrics

Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms.

BACKGROUND: The activation of follicle stimulating hormone receptor (FSHR) by FSH and the consequent downstream signaling activities are crucial for reproductive health. The role of FSHR in tumor progression as well as osteoporosis advancement has also been well established. Currently, steroid preparations of estrogen and progesterone are being used for managing fertility, in spite of the harmful ...

Prediction of future cognitive impairment among the community elderly: A machine-learning based approach.

The early detection of cognitive impairment is a key issue among the elderly. Although neuroimaging, genetic, and cerebrospinal measurements show promising results, high costs and invasiveness hinder their widespread use. Predicting cognitive impairment using easy-to-collect variables by non-invasive methods for community-dwelling elderly is useful prior to conducting such a comprehensive evaluati...

Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification.

Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at r...

Towards end-to-end likelihood-free inference with convolutional neural networks.

Complex simulator-based models with non-standard sampling distributions require sophisticated design choices for reliable approximate parameter infere...

Hybrid multivariate pattern analysis combined with extreme learning machine for Alzheimer's dementia diagnosis using multi-measure rs-fMRI spatial patterns.

BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) is essential for timely treatment. Machine learning and mu...

End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning.

We study active object tracking, where a tracker takes visual observations (i.e., frame sequences) as input and produces the corresponding camera cont...

Random forest prediction of Alzheimer's disease using pairwise selection from time series data.

Time-dependent data collected in studies of Alzheimer's disease usually has missing and irregularly sampled data points. For this reason time series m...

New-Onset Alzheimer's Disease and Normal Subjects 100% Differentiated by P300.

Previous work has suggested that evoked potential analysis might allow the detection of subjects with new-onset Alzheimer's disease, which would be us...

New Approaches for the Treatment of Delirium: A Case for Robotic Pets.

Acceleration of spleen segmentation with end-to-end deep learning method and automated pipeline.

Delineation of Computed Tomography (CT) abdominal anatomical structure, specifically spleen segmentation, is useful for not only measuring tissue volu...

Using machine learning to optimize selection of elderly patients for endovascular thrombectomy.

BACKGROUND: Endovascular thrombectomy (ET) is the standard of care for treatment of acute ischemic stroke (AIS) secondary to large vessel occlusion. T...

Implicit Irregularity Detection Using Unsupervised Learning on Daily Behaviors.

The irregularity detection of daily behaviors for the elderly is an important issue in homecare. Plenty of mechanisms have been developed to detect th...

Multi-task exclusive relationship learning for alzheimer's disease progression prediction with longitudinal data.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, m...

RNN-based longitudinal analysis for diagnosis of Alzheimer's disease.

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and other mental functions. Magnetic reso...

Development of a cardiac-centered frailty ontology.

BACKGROUND: A Cardiac-centered Frailty Ontology can be an important foundation for using NLP to assess patient frailty. Frailty is an important consid...

A Novel Protein Subcellular Localization Method With CNN-XGBoost Model for Alzheimer's Disease.

The disorder distribution of protein in the compartment or organelle leads to many human diseases, including neurodegenerative diseases such as Alzhei...

Network-Based Assessment of Adverse Drug Reaction Risk in Polypharmacy Using High-Throughput Screening Data.

The risk of adverse drug reactions increases in a polypharmacology setting. High-throughput drug screening with transcriptomics applied to human cells...

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and in...

Machine learning methods for detecting urinary tract infection and analysing daily living activities in people with dementia.

Dementia is a neurological and cognitive condition that affects millions of people around the world. At any given time in the United Kingdom, 1 in 4 h...

A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.

Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's disease (AD), while other MCI types tend to remain stable ove...