Geriatrics

Latest AI and machine learning research in geriatrics for healthcare professionals.

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A model to forecast the two-year variation of subjective wellbeing in the elderly population.

BACKGROUND: The ageing global population presents significant public health challenges, especially i...

IMH-Net: a convolutional neural network for end-to-end EEG motor imagery classification.

As the main component of Brain-computer interface (BCI) technology, the classification algorithm bas...

Treating drug-resistant tuberculosis in an era of shorter regimens: Insights from rural South Africa.

BACKGROUND: Progressive interventions have recently improved programmatic outcomes in drug-resistant...

LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality.

Age is closely related to human health and disease risks. However, chronologically defined age often...

Implementing link prediction in protein networks via feature fusion models based on graph neural networks.

MOTIVATION: Protein-protein interactions serve as the cornerstone for various biochemical processes ...

Artificial intelligence: Machine learning approach for screening large database and drug discovery.

Recent research in drug discovery dealing with many faces difficulties, including development of new...

An End-to-End Platform for Digital Pathology Using Hyperspectral Autofluorescence Microscopy and Deep Learning-Based Virtual Histology.

Conventional histopathology involves expensive and labor-intensive processes that often consume tiss...

Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care.

It is important for older and disabled people who live alone to be able to cope with the daily chall...

identifies gender disparities in scientific peer review.

The peer review process is a critical step in ensuring the quality of scientific research. However, ...

Deep Learning-Based Ensembling Technique to Classify Alzheimer's Disease Stages Using Functional MRI.

The major issue faced by elderly people in society is the loss of memory, difficulty learning new th...

Algorithmic Fairness of Machine Learning Models for Alzheimer Disease Progression.

IMPORTANCE: Predictive models using machine learning techniques have potential to improve early dete...

In-hospital fall prediction using machine learning algorithms and the Morse fall scale in patients with acute stroke: a nested case-control study.

BACKGROUND: Falls are one of the most common accidents in medical institutions, which can threaten t...

Employing Deep-Learning Approach for the Early Detection of Mild Cognitive Impairment Transitions through the Analysis of Digital Biomarkers.

Mild cognitive impairment (MCI) is the precursor to the advanced stage of Alzheimer's disease (AD), ...

Deep learning-based grading of white matter hyperintensities enables identification of potential markers in multi-sequence MRI data.

BACKGROUND: White matter hyperintensities (WMHs) are widely-seen in the aging population, which are ...

Unveiling Osteoporosis Through Radiomics Analysis of Hip CT Imaging.

RATIONALE AND OBJECTIVES: This study aims to investigate the use of radiomics analysis of hip CT ima...

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis.

BACKGROUND: The relationship between physical function, musculoskeletal disorders and sarcopenia is ...

Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning.

OBJECTIVE: To develop and evaluate a fully automated method based on deep learning and phantomless i...

Cholesterol Levels, Hormone Replacement Therapy, and Incident Dementia among Older Adult Women.

Previous studies revealed that hormone replacement therapy (HRT) probably has a protective effect fo...

Next-generation cognitive assessment: Combining functional brain imaging, system perturbations and novel equipment interfaces.

Conventional cognitive assessment is widely used in clinical and research settings, in educational i...

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