Geriatrics

Machine learning studies on major brain diseases: 5-year trends of 2014-2018.

In the recent 5 years (2014-2018), there has been growing interest in the use of machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic lesion changes within the area of neuroradiology. However, to date, the majority of research trend and current status have not been clearly illuminated in the neuroradiology field. More than 1000 papers have been published during ...

Mobile detection of autism through machine learning on home video: A development and prospective validation study.

BACKGROUND: The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access to therapy. We hypothesize that the use of machine learning analysis on home video can speed the diagnosis without compromising accuracy. We have ana...

Inter-subject transfer learning with an end-to-end deep convolutional neural network for EEG-based BCI.

OBJECTIVE: Despite the effective application of deep learning (DL) in brain-computer interface (BCI) systems, the successful execution of this techniq...

Pulmonary Function Testing in Elderly Patients Treated for a Myasthenia Gravis Exacerbation.

BACKGROUND AND PURPOSE: Pulmonary function testing is a standard part of care for patients admitted to hospital with a myasthenia gravis exacerbation....

Comparison of Muscular Activity and Movement Performance in Robot-Assisted and Freely Performed Exercises.

End-effector-based robotic systems are, in particular, suitable for extending physical therapy in stroke rehabilitation. An adequate therapy and thus ...

A nurse-driven method for developing artificial intelligence in "smart" homes for aging-in-place.

OBJECTIVES: To offer practical guidance to nurse investigators interested in multidisciplinary research that includes assisting in the development of ...

Artificial intelligence for aging and longevity research: Recent advances and perspectives.

The applications of modern artificial intelligence (AI) algorithms within the field of aging research offer tremendous opportunities. Aging is an almo...

Machine learning based classification of cells into chronological stages using single-cell transcriptomics.

Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for...

Novel Effective Connectivity Inference Using Ultra-Group Constrained Orthogonal Forward Regression and Elastic Multilayer Perceptron Classifier for MCI Identification.

Mild cognitive impairment (MCI) detection is important, such that appropriate interventions can be imposed to delay or prevent its progression to seve...

Using telepresence for social connection: views of older people with dementia, families, and health professionals from a mixed methods pilot study.

To explore the acceptability of telepresence robots in dementia care from the perspectives of people with dementia, family carers, and health profess...

Use of a robotic walking aid in rehabilitation to reduce fear of falling is feasible and acceptable from the end user's perspective: A randomised comparative study.

Objectives To determine the acceptability and feasibility of the use of a robotic walking aid to support the work of physiotherapists in reducing fear...

Non-directed bronchial lavage is a safe method for sampling the respiratory tract in critically ill patient.

Ventilated patients are at risk of acquiring ventilator-associated pneumonia. Various techniques are available for diagnosing ventilator-associated pn...

Multi-level features combined end-to-end learning for automated pathological grading of breast cancer on digital mammograms.

We propose to discriminate the pathological grades directly on digital mammograms instead of pathological images. An end-to-end learning algorithm bas...

Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks.

Magnetic resonance imaging (MRI) has been proposed as a complimentary method to measure bone quality and assess fracture risk. However, manual segment...

Improved model adaptation approach for recognition of reduced-frame-rate continuous speech.

In distributed speech recognition applications, the front-end device that stands for any handheld electronic device like smartphones and personal digi...

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using F-FDG PET of the Brain.

Purpose To develop and validate a deep learning algorithm that predicts the final diagnosis of Alzheimer disease (AD), mild cognitive impairment, or n...

A unified non-linear approach based on recurrence quantification analysis and approximate entropy: application to the classification of heart rate variability of age-stratified subjects.

This paper presents a unified approach based on the recurrence quantification analysis (RQA) and approximate entropy (ApEn) for the classification of ...

Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis.

In this article, the authors aim to maximally utilize multimodality neuroimaging and genetic data for identifying Alzheimer's disease (AD) and its pro...

Will machine learning end the viability of radiology as a thriving medical specialty?

There have been tremendous advances in artificial intelligence (AI) and machine learning (ML) within the past decade, especially in the application of...

Sense classification of shallow discourse relations with focused RNNs.

Understanding the sense of discourse relations between segments of text is essential to truly comprehend any natural language text. Several automated ...