Geriatrics

Explainable artificial intelligence for early Alzheimer's diagnosis using enhanced grey relational features and multimodal data.

Alzheimer's disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has enhanced the diagnostic accuracy of machine learning, there is a major concern about striking a balance between predictive performance and interpretability. The proposed study presents an inter...

Use of Conventional Artificial Intelligence Methods in the Identification of Frailty: A Scoping Review.

BACKGROUND: Early identification and management of frailty are crucial, yet its detection in early stages remains difficult for clinicians. Artificial intelligence (AI) has emerged as a promising tool in healthcare. However, the absence of a standard frailty definition and diversity of AI methods create a need for a comprehensive review. This study examines the clinical tools and conceptual framew...

Managing maternity: Moving care, not patients, using artificial intelligence (AI), internet-of-things (IOT) and point-of-care testing (POCT) devices.

The integration of artificial intelligence (AI) into healthcare is accelerating and maternity care is at a pivotal moment for the strategic implementa...

Integration of detection and tracking networks for automated rib multiplanar reconstruction: a feasibility study for fracture diagnosis.

OBJECTIVE: Rib fractures are common yet time-consuming to diagnose. This study explores automation via multiplanar reconstruction and intelligent dete...

Deep survival modelling to predict future cognitive impairment in unimpaired adults.

BACKGROUND: Predicting Alzheimer's disease (AD)-related cognitive impairment (CI) among cognitively normal (CN) adults enables meaningful disease modi...

Transforming Care: Nursing Research, EBP, and Innovation: Celebrating the 10-Year Anniversary of the Kaiser Permanente Scholars Academy.

Kaiser Permanente Northern California (KPNCAL) has a long-standing commitment to advancing nursing excellence through workforce development, professio...

[Magnetic resonance imaging in dementia].

Magnetic resonance imaging (MRI) plays a pivotal role in the diagnostic work-up of dementia. In addition to excluding secondary and potentially treata...

Claustrum and Hippocampus Segmentation-Based Alzheimer's Disease Identification Model Using RoT-Kmeans and CoLU-CNN.

Alzheimer's disease (AD) is a dementia disease that causes loss of cognitive functions. Also, it is a noncurable disease. However, early diagnosis and...

Tissue morphology predicts telomere shortening in human tissues.

We present TLPath, a deep learning framework that predicts bulk-tissue telomere length from tissue morphology extracted from routine histopathology im...

Salivary metabolomics for early detection of vascular contributions to cognitive impairment and dementia: Exploring microbiome dysbiosis and sex differences.

BackgroundVascular factors contribute to dementia in approximately 20 million individuals, notably in vascular contributions to cognitive impairment a...

Machine Learning Prediction of Progression to Dialysis in Patients With Polycystic Kidney Disease: Population-Based Retrospective Cohort Study.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), characterized by progressive cyst growth and renal decline, is the leading genetic c...

Gait and movement analysis for discrimination between people with dementia and healthy control persons based on pose estimation and machine learning.

BackgroundDementia disorders are affecting millions of people globally, characterized by memory loss, communication difficulties, and motor function d...

Robotic Pets in Hospitals: Fostering Connection.

Acute care hospitals often fail to meet the relational needs of older adults with dementia, for whom many environmental stressors can exacerbate behav...

The iterative shrinkage thresholding algorithm reveals dynamic aging trajectories of human T lymphocytes via multidimensional spectral flow cytometry analysis.

Immunosenescence is a fundamental hallmark of aging, characterized by differential susceptibility across immune cell lineages. T lymphocytes are parti...

A multimodal feature disentanglement model for lymphadenopathy diagnosis based on BUS and CDFI ultrasound videos: a retrospective, prospective, multicenter study.

OBJECTIVES: This study developed and validated a deep learning model for diagnosing lymphadenopathy (LA) using B-mode ultrasound (BUS) and color Doppl...

Certainty Language Use in Pediatric Radiology: A Single-Institution Analysis.

BACKGROUND: Radiologists often employ diagnostic certainty phrases (DCPs) to convey levels of confidence in imaging interpretations. Prior research in...

Unsupervised identification of muscle phenotypes in adults with obesity: a data-driven framework for the identification of sarcopenia in absence of a gold standard.

BACKGROUND: Sarcopenia is characterized by progressive loss of skeletal muscle mass and strength and is associated with increased disability and morta...

Use of artificial intelligence and radiomics for diagnosis and prediction of osteoporotic fractures: a systematic review.

AIM: Osteoporosis (OP) is a prevalent metabolic bone disease causing millions of fractures annually, leading to significant healthcare and economic bu...

Predicting cognitive frailty in older adults: an explainable machine learning model integrating radiomics and clinical features.

Estimating cognitive function score from mild cognitive impairment to moderate dementia using a hybrid model combining plasma biomarkers with electroencephalogram signal.

BackgroundPredicting cognitive function across dementia stages remains challenging. Plasma biomarkers and electroencephalogram (EEG) features may prov...