Geriatrics

The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.

INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease ...

Robotic Rehabilitation in Spinal Cord Injury: A Pilot Study on End-Effectors and Neurophysiological Outcomes.

Robot-aided gait training (RAGT) has been implemented to provide patients with spinal cord injury (S...

An invited commentary on "Robotic pancreaticoduodenectomy in elderly and younger patients: A retrospective cohort study" [Int. J. Surg. (2020) Epub ahead of print].

An invited commentary on: "Robotic pancreaticoduodenectomy in elderly and young patients: A retrospective cohort study" (International Journal of Surgery 2020; 81:61-65).

Multi-slice representational learning of convolutional neural network for Alzheimer's disease classification using positron emission tomography.

BACKGROUND: Alzheimer's Disease (AD) is a degenerative brain disorder that often occurs in people ov...

Disentangling time series between brain tissues improves fMRI data quality using a time-dependent deep neural network.

Functional MRI (fMRI) is a prominent imaging technique to probe brain function, however, a substanti...

A Methodology to Differentiate Parkinson's Disease and Aging Speech Based on Glottal Flow Acoustic Analysis.

Speech is controlled by axial neuromotor systems, therefore, it is highly sensitive to the effects o...

Knowledge-Based Decision Support in Healthcare via Near Field Communication.

The benefits of automatic identification technologies in healthcare have been largely recognized. Ne...

Application of Machine Learning Methods in Nursing Home Research.

A machine learning (ML) system is able to construct algorithms to continue improving predictions an...

Microbial contamination and efficacy of disinfection procedures of companion robots in care homes.

BACKGROUND: Paro and other robot animals can improve wellbeing for older adults and people with deme...

A Comparative Study of Supervised Machine Learning Algorithms for the Prediction of Long-Range Chromatin Interactions.

The role of three-dimensional genome organization as a critical regulator of gene expression has bec...

Applications of Artificial Intelligence in Musculoskeletal Imaging: From the Request to the Report.

Artificial intelligence (AI) will transform every step in the imaging value chain, including interpr...

Using Machine Learning to Make Predictions in Patients Who Fall.

BACKGROUND: As the population ages, the incidence of traumatic falls has been increasing. We hypothe...

Predicting the progression of mild cognitive impairment to Alzheimer's disease by longitudinal magnetic resonance imaging-based dictionary learning.

OBJECTIVE: Efficient prediction of the progression of mild cognitive impairment (MCI) to Alzheimer's...

A robust and interpretable end-to-end deep learning model for cytometry data.

Cytometry technologies are essential tools for immunology research, providing high-throughput measur...

Role of Assistive Robots in the Care of Older People: Survey Study Among Medical and Nursing Students.

BACKGROUND: Populations are aging at an alarming rate in many countries around the world. There has ...

Long-distance disorder-disorder relation extraction with bootstrapped noisy data.

OBJECTIVE: Artificial intelligence in healthcare increasingly relies on relations in knowledge graph...

Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study.

BACKGROUND: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effec...

Identifying sarcopenia in advanced non-small cell lung cancer patients using skeletal muscle CT radiomics and machine learning.

BACKGROUND: Sarcopenia has been confirmed as a poor prognostic indicator of lung cancer. However, th...

VEPAD - Predicting the effect of variants associated with Alzheimer's disease using machine learning.

INTRODUCTION: Alzheimer's disease (AD) is a complex and heterogeneous disease that affects neuronal ...

Predicting Alzheimer's disease progression using deep recurrent neural networks.

Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is impor...