Geriatrics

Artificial intelligence insights into osteoporosis: assessing ChatGPT's information quality and readability.

UNLABELLED: Accessible, accurate information, and readability play crucial role in empowering individuals managing osteoporosis. This study showed that the responses generated by ChatGPT regarding osteoporosis had serious problems with quality and were at a level of complexity that that necessitates an educational background of approximately 17 years.

Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptoms.

BACKGROUND: Predicting future Alzheimer's disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as measured by magnetic resonance imaging (MRI) could potentially contribute when making such predictions. It is unclear if the predictive performance of MRI can be...

Age-related changes in human brain functional connectivity using graph theory and machine learning techniques in resting-state fMRI data.

Aging is the basis of neurodegeneration and dementia that affects each endemic in the body. Normal aging in the brain is associated with progressive s...

Application of artificial intelligence in active assisted living for aging population in real-world setting with commercial devices - A scoping review.

BACKGROUND: The aging population is steadily increasing, posing new challenges and opportunities for healthcare systems worldwide. Technological advan...

Predicting the onset of end-stage knee osteoarthritis over two- and five-years using machine learning.

OBJECTIVE: Identifying participants who will progress to advanced stage in knee osteoarthritis (KOA) trials remains a significant challenge. Current t...

Utilizing Siamese 4D-AlzNet and Transfer Learning to Identify Stages of Alzheimer's Disease.

Alzheimer's disease (AD) is the general form of dementia, leading to a progressive neurological disorder characterized by memory loss due to brain cel...

Authorship gender among articles about artificial intelligence in breast imaging.

RATIONALE AND OBJECTIVES: The purpose of this study is to investigate the variance of women authors, specifically first and senior authorship among pe...

End-to-end deep learning approach to mouse behavior classification from cortex-wide calcium imaging.

Deep learning is a powerful tool for neural decoding, broadly applied to systems neuroscience and clinical studies. Interpretable and transparent mode...

Socially Assistive Robots for patients with Alzheimer's Disease: A scoping review.

BACKGROUND: The most common form of dementia, Alzheimer's Disease (AD), is challenging for both those affected as well as for their care providers, an...

Automatic and robust estimation of sex and chronological age from panoramic radiographs using a multi-task deep learning network: a study on a South Korean population.

Sex and chronological age estimation are crucial in forensic investigations and research on individual identification. Although manual methods for sex...

Facilitators and barriers to codesigning social robots with older adults with dementia: a scoping review protocol.

INTRODUCTION: Social robots including telepresence robots have emerged as potential support in dementia care. However, the effectiveness of these robo...

Nursing Perceptions of Robotic Technology in Healthcare: A Pretest-Posttest Survey Analysis Using an Educational Video.

OCCUPATIONAL APPLICATIONSWe used a survey to evaluate the perceptions of nurses and nursing students on robotic technology for nursing care before and...

Perspective analysis of assistive robots for elderly in India.

PURPOSE: Assistive technology for elderly are advancing, and this study aimed to analyse the Indian perspective on utilising assistive robot technolog...

Deep Learning-Driven Exploration of Pyrroloquinoline Quinone Neuroprotective Activity in Alzheimer's Disease.

Alzheimer's disease (AD) is a pressing concern in neurodegenerative research. To address the challenges in AD drug development, especially those targe...

ChatGPT in Pediatrics: Unraveling its Significance as a Clinical Decision Support Tool.

The integration of artificial intelligence in pediatrics holds transformative potential, reshaping healthcare through innovative approaches to diagnos...

Organ-specific biological clocks: Ageotyping for personalized anti-aging medicine.

Aging is a complex multidimensional, progressive remodeling process affecting multiple organ systems. While many studies have focused on studying agin...

Coupling speckle noise suppression with image classification for deep-learning-aided ultrasound diagnosis.

. During deep-learning-aided (DL-aided) ultrasound (US) diagnosis, US image classification is a foundational task. Due to the existence of serious spe...

LGDNet: local feature coupling global representations network for pulmonary nodules detection.

Detection of suspicious pulmonary nodules from lung CT scans is a crucial task in computer-aided diagnosis (CAD) systems. In recent years, various dee...

On the pitfalls of Batch Normalization for end-to-end video learning: A study on surgical workflow analysis.

Batch Normalization's (BN) unique property of depending on other samples in a batch is known to cause problems in several tasks, including sequence mo...

Prediction of cognitive impairment using higher order item response theory and machine learning models.

Timely detection of cognitive impairment (CI) is critical for the wellbeing of elderly individuals. The MyCog assessment employs two validated iPad-ba...