AIMC Topic: Aged

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Deep learning model for predicting the survival of patients with primary gastrointestinal lymphoma based on the SEER database and a multicentre external validation cohort.

Journal of cancer research and clinical oncology
PURPOSE: Due to the rarity of primary gastrointestinal lymphoma (PGIL), the prognostic factors and optimal management of PGIL have not been clearly defined. We aimed to establish prognostic models using a deep learning algorithm for survival predicti...

Deep Learning-Assisted Gait Parameter Assessment for Neurodegenerative Diseases: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Neurodegenerative diseases (NDDs) are prevalent among older adults worldwide. Early diagnosis of NDD is challenging yet crucial. Gait status has been identified as an indicator of early-stage NDD changes and can play a significant role in...

Detection of preceding sleep apnea using ECG spectrogram during CPAP titration night: A novel machine-learning and bag-of-features framework.

Journal of sleep research
Obstructive sleep apnea (OSA) has a heavy health-related burden on patients and the healthcare system. Continuous positive airway pressure (CPAP) is effective in treating OSA, but adherence to it is often inadequate. A promising solution is to detect...

Types, functions and mechanisms of robot-assisted intervention for fall prevention: A systematic scoping review.

Archives of gerontology and geriatrics
BACKGROUND: Any individual may experience accidental falls, particularly older adults. Although robots can prevent falls, knowledge of their fall-preventive use is limited.

Can the Electronic Health Record Predict Risk of Falls in Hospitalized Patients by Using Artificial Intelligence? A Meta-analysis.

Computers, informatics, nursing : CIN
Because of an aging population worldwide, the increasing prevalence of falls and their consequent injuries are becoming a safety, health, and social-care issue among elderly people. We conducted a meta-analysis to investigate the benchmark of predict...

Deep Learning Reconstruction Plus Single-Energy Metal Artifact Reduction for Supra Hyoid Neck CT in Patients With Dental Metals.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
We investigated the effect of deep learning reconstruction (DLR) plus single-energy metal artifact reduction (SEMAR) on neck CT in patients with dental metals, comparing it with DLR and with hybrid iterative reconstruction (Hybrid IR)-SEMAR. In thi...

System Based on Artificial Intelligence Edge Computing for Detecting Bedside Falls and Sleep Posture.

IEEE journal of biomedical and health informatics
Bedside falls and pressure ulcers are crucial issues in geriatric care. Although many bedside monitoring systems have been proposed, they are limited by the computational complexity of their algorithms. Moreover, most of the data collected by the sen...

Classification and deep-learning-based prediction of Alzheimer disease subtypes by using genomic data.

Translational psychiatry
Late-onset Alzheimer's disease (LOAD) is the most common multifactorial neurodegenerative disease among elderly people. LOAD is heterogeneous, and the symptoms vary among patients. Genome-wide association studies (GWAS) have identified genetic risk f...

Optimising the care for older persons with complex chronic conditions in home care and nursing homes: design and protocol of I-CARE4OLD, an observational study using real-world data.

BMJ open
INTRODUCTION: In ageing societies, the number of older adults with complex chronic conditions (CCCs) is rapidly increasing. Care for older persons with CCCs is challenging, due to interactions between multiple conditions and their treatments. In home...

Acceptance of social assistant robots for the older adults living in the community in China.

Geriatric nursing (New York, N.Y.)
BACKGROUND: Social assistant robots (SARs) are an important part of providing high quality health and social care for older people, and are an effective measure to promote the development of smart aging. Therefore, it is important to understand the f...