AIMC Topic: Aged, 80 and over

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Using a Robot to Address the Well-Being, Social Isolation, and Loneliness of Care Home Residents via Video Calls: Qualitative Feasibility Study.

JMIR formative research
BACKGROUND: About 40,000 people are living in Norwegian care homes, where a majority are living with a dementia diagnosis. Social isolation and loneliness are common issues affecting care home residents' quality of life. Due to visitation restriction...

Machine learning-based survival models for predicting rehospitalization of older hip fracture patients: a retrospective cohort study.

BMC musculoskeletal disorders
PURPOSE: To evaluate machine learning-based survival model roles in predicting rehospitalization after hip fractures to improve reduce the burden on the healthcare system.

Concordance of ChatGPT artificial intelligence decision-making in colorectal cancer multidisciplinary meetings: retrospective study.

BJS open
BACKGROUND: The objective of this study was to evaluate the concordance between therapeutic recommendations proposed by a multidisciplinary team meeting and those generated by a large language model (ChatGPT) for colorectal cancer. Although multidisc...

Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study.

Journal of medical Internet research
BACKGROUND: Early detection is clinically crucial for the strategic handling of sarcopenia, yet the screening process, which includes assessments of muscle mass, strength, and function, remains complex and difficult to access.

A Preliminary Usability Evaluation of an Artificial Intelligence-Based, Motion-Detecting Wearable Device: The Geriatric Functional Assessment System.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Physical function is a key determinant of independence among older adults. Yet, there are barriers to assessing physical function in clinic. We developed a wearable geriatric functional assessment system (GFAS) that quickly and effortless...

Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH.

Respiratory research
BACKGROUND: Classification of the etiologies of pleural effusion is a critical challenge in clinical practice. Traditional diagnostic methods rely on a simple cut-off method based on the laboratory tests. However, machine learning (ML) offers a novel...

[Evaluation of the possibility of using neural networks for automatic diagnostics of obstructive urination].

Urologiia (Moscow, Russia : 1999)
INTRODUCTION: Obstructive type of urination requires accurate and timely diagnosis to prevent complications and improve the quality of life of patients. Traditional diagnostic methods such as uroflowmetry, although they remain the standard, have thei...

The role of the sacroiliac joint in sex estimation: Analysis of morphometry and variation types using machine learning techniques.

Legal medicine (Tokyo, Japan)
This study aimed to evaluate the potential of machine learning algorithms in sex estimation by going beyond the traditional two-dimensional (2D) measurements of the pelvic bone, predominantly preferred in sex prediction, by including measurement data...

The Association Between Hepatocellular Carcinoma and Gastrointestinal Adenocarcinoma: Is This a New Syndrome in Patients With Cirrhosis? A Case Series.

Cancer reports (Hoboken, N.J.)
AIM: This case series aimed to explore the occurrence of synchronous hepatocellular carcinoma (HCC) and gastrointestinal adenocarcinoma in cirrhotic patients and to propose a potential common pathogenic mechanism.

Dual-stream algorithms for dementia detection: Harnessing structured and unstructured electronic health record data, a novel approach to prevalence estimation.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Identifying individuals with dementia is crucial for prevalence estimation and service planning, but reliable, scalable methods are lacking. We developed novel set algorithms using both structured and unstructured electronic health reco...