Geriatrics

A new method to predict anomaly in brain network based on graph deep learning.

Functional magnetic resonance imaging a neuroimaging technique which is used in brain disorders and ...

Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.

Delineation of organs at risk (OARs) is important but time consuming for radiotherapy planning. Auto...

Machine Learning for Predictive Modeling of 90-day Readmission, Major Medical Complication, and Discharge to a Facility in Patients Undergoing Long Segment Posterior Lumbar Spine Fusion.

STUDY DESIGN: Retrospective case control study.

Assistive robots in the homes of aging adults.

Brief communication: Three errors and two problems in a recent paper: gazeNet: End-to-end eye-movement event detection with deep neural networks (Zemblys, Niehorster, and Holmqvist, 2019).

Zemblys et al. (Behavior Research Methods, 51(2), 840-864, 2019) reported on a method for the classi...

Machine Learning Analysis Reveals Novel Neuroimaging and Clinical Signatures of Frailty in HIV.

BACKGROUND: Frailty is an important clinical concern for the aging population of people living with ...

Fall Detector Adapted to Nursing Home Needs through an Optical-Flow based CNN.

Fall detection in specialized homes for the elderly is challenging. Vision-based fall detection solu...

An Infrared Array Sensor-Based Method for Localizing and Counting People for Health Care and Monitoring.

To build a system for monitoring elderly people living alone, an important step needs to be done: id...

Detecting falls and estimation of daily habits with depth images using machine learning algorithms.

Different approaches have been proposed in the literature to detect the fall of an elderly person. I...

Segmentation of Tau Stained Alzheimers Brain Tissue Using Convolutional Neural Networks.

Alzheimers disease is characterized by complex changes in brain tissue including the accumulation of...

End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences.

Dynamic reconstructions (3D+T) of coronary arteries could give important perfusion details to clinic...

A Two Cascaded Network Integrating Regional-based YOLO and 3D-CNN for Cerebral Microbleeds Detection.

Cerebral Microbleeds (CMBs) are small chronic brain hemorrhages, which have been considered as diagn...

Predicting Age with Deep Neural Networks from Polysomnograms.

The aim of this study was to design a new deep learning framework for end-to-end processing of polys...

Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study.

OBJECTIVE: Machine learning models trained on electronic health records have achieved high prognosti...

Can robots express facial emotions dominantly enough for use in dementia care?

Mobile Robotic Telepresence Between Hospital and School: Lessons Learned.

If a pupil falls seriously ill, it is not only a shock for the pupil himself or herself, but also fo...

Evaluating Performance and Interpretability of Machine Learning Methods for Predicting Delirium in Gerontopsychiatric Patients.

Delirium is an acute mental disturbance that particularly occurs during hospital stay. Current clini...

Integrating Socially Assistive Robots into Japanese Nursing Care.

This paper presents experiences of integrating assistive robots in Japanese nursing care through sem...

Social Robots for Elderly Care: An Inventory of Promising Use Cases and Business Models.

This paper discusses a study that aimed to elicit promising application areas and potential business...

Investigating the Barriers to Physician Adoption of an Artificial Intelligence- Based Decision Support System in Emergency Care: An Interpretative Qualitative Study.

The development of artificial intelligence (AI) systems to support diagnostic decision-making is rap...

Using Unsupervised Learning to Identify Clinical Subtypes of Alzheimer's Disease in Electronic Health Records.

Identifying subtypes of Alzheimer's Disease (AD) can lead towards the creation of personalized inter...