AIMC Topic: Aged

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Predicting the efficacy of bevacizumab on peritumoral edema based on imaging features and machine learning.

Scientific reports
This study proposes a novel approach to predict the efficacy of bevacizumab (BEV) in treating peritumoral edema in metastatic brain tumor patients by integrating advanced machine learning (ML) techniques with comprehensive imaging and clinical data. ...

Association between urinary cadmium levels and increased gallstone disease in US adults.

Scientific reports
Heavy metal exposure is acknowledged as a risk factor for poor health. However, the effect of heavy metal exposure on the prevalence of gallstones is still unknown. Therefore, we investigated the relationship between heavy metal concentrations and th...

Prediction of the functional outcome of intensive inpatient rehabilitation after stroke using machine learning methods.

Scientific reports
An accurate and reliable functional prognosis is vital to stroke patients addressing rehabilitation, to their families, and healthcare providers. This study aimed at developing and validating externally patient-wise prognostic models of the global fu...

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...

Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning.

Journal of neuroengineering and rehabilitation
BACKGROUND: Knee osteoarthritis (KOA) is a prevalent chronic disease worldwide, and traditional treatment methods lack personalized adjustment for individual patient differences and cannot meet the needs of personalized treatment.

Validation of artificial intelligence algorithm LuxIA for screening of diabetic retinopathy from a single 45° retinal colour fundus images: the CARDS study.

BMJ open ophthalmology
OBJECTIVE: This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from a single 45° colour fundus image of patients with diabetes mellitus (DM, type 1 or type 2) in Spain....

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.

EEG-based Signatures of Schizophrenia, Depression, and Aberrant Aging: A Supervised Machine Learning Investigation.

Schizophrenia bulletin
BACKGROUND: Electroencephalography (EEG) is a noninvasive, cost-effective, and robust tool, which directly measures in vivo neuronal mass activity with high temporal resolution. Combined with state-of-the-art machine learning (ML) techniques, EEG rec...

Comparing Artificial Intelligence-Generated and Clinician-Created Personalized Self-Management Guidance for Patients With Knee Osteoarthritis: Blinded Observational Study.

Journal of medical Internet research
BACKGROUND: Knee osteoarthritis is a prevalent, chronic musculoskeletal disorder that impairs mobility and quality of life. Personalized patient education aims to improve self-management and adherence; yet, its delivery is often limited by time const...