Geriatrics

Learning to Detect Cognitive Impairment through Digital Games and Machine Learning Techniques.

OBJECTIVE: Alzheimer's disease (AD) is one of the most prevalent diseases among the adult population...

Towards End-to-End ECG Classification With Raw Signal Extraction and Deep Neural Networks.

This paper proposes deep learning methods with signal alignment that facilitate the end-to-end class...

Dialogue Systems and Conversational Agents for Patients with Dementia: The Human-Robot Interaction.

This study aimed to identify and describe the fundamental characteristics of spoken dialogue systems...

Instance-Based Representation Using Multiple Kernel Learning for Predicting Conversion to Alzheimer Disease.

The early detection of Alzheimer's disease and quantification of its progression poses multiple diff...

A Novel Deep Learning Framework on Brain Functional Networks for Early MCI Diagnosis.

Although alternations of brain functional networks (BFNs) derived from resting-state functional magn...

Temporal Correlation Structure Learning for MCI Conversion Prediction.

In Alzheimer's research, Mild Cognitive Impairment (MCI) is an important intermediate stage between ...

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis.

In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain disease...

"You can tell by the way I use my walk." Predicting the presence of cognitive load with gait measurements.

BACKGROUND: There is considerable evidence that a person's gait is affected by cognitive load. Resea...

Effectiveness of bisphosphonate combined with activated vitamin D in patients with aromatase inhibitor-induced osteoporosis after breast cancer operation.

OBJECTIVES: We compared the effectiveness of bisphosphonates combined with activated vitamin D admin...

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging I...

An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA.

One of the methods for stratifying different molecular classes of breast cancer is the Nottingham pr...

Should Artificial Intelligence Augment Medical Decision Making? The Case for an Autonomy Algorithm.

A significant proportion of elderly and psychiatric patients do not have the capacity to make health...

Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices.

Artificial Intelligence (AI) has long promised to increase healthcare affordability, quality and acc...

Social Robots for People with Aging and Dementia: A Systematic Review of Literature.

Using high-dimensional machine learning methods to estimate an anatomical risk factor for Alzheimer's disease across imaging databases.

INTRODUCTION: The main goal of this work is to investigate the feasibility of estimating an anatomic...

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data.

A large number of papers have introduced novel machine learning and feature extraction methods for a...

Identification of novel immune-relevant drug target genes for Alzheimer's Disease by combining ontology inference with network analysis.

AIMS: Alzheimer's disease (AD) is one of the leading causes of death in elderly people. Its pathogen...

Re: Modified Frailty Index Associated with Clavien-Dindo IV Complications in Robot-Assisted Radical Prostatectomies: A Retrospective Study.

End-to-End Representation Learning for Chemical-Chemical Interaction Prediction.

Chemical-chemical interaction (CCI) plays a major role in predicting candidate drugs, toxicities, th...

Development and Validation of an Electronic Health Record-Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment.

IMPORTANCE: Current methods for identifying hospitalized patients at increased risk of delirium requ...

Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism.

Although standard behavioral interventions for autism spectrum disorder (ASD) are effective therapie...