AIMC Topic: Quality of Life

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Explainable machine learning identifies key quality-of-life-related predictors of arthritis status: evidence from the China health and retirement longitudinal study.

Health and quality of life outcomes
BACKGROUND: Arthritis is a prevalent chronic disease substantially impacting patients' quality of life (QoL). While identifying key determinants associated with arthritis is critical for targeted interventions, traditional statistical methods often s...

Robot-assisted gait training after severe traumatic brain injury for walking ability and social participation: protocol for a feasibility study.

BMJ open
INTRODUCTION: Traumatic brain injury (TBI) is a traumatic head injury that can lead to gait-related disabilities, and exoskeleton training may be beneficial for the recovery of this function in these patients. The objective of this study is to determ...

Platform Technology for Extended Reality Biofeedback Training Under Operant Conditioning for Functional Limb Weakness: Protocol for the Coproduction of an at-Home Solution (React2Home).

JMIR research protocols
BACKGROUND: Functional neurological disorder (FND), including functional movement disorders (FMDs), arises from disruptions in the perception-action cycle, where maladaptive cognitive learning processes reduce the sense of agency and motor control. F...

A smart secure virtual reality immersive application for alzheimer's and dementia patients.

Scientific reports
Alzheimer's disease (AD) poses significant challenges for the elderly, leading to cognitive decline, social isolation, and lower quality of life. Current interventions often require cumbersome wearable devices e.g. the camera-based monitoring that ma...

Effectiveness of spiritual health-based interventions in improving health indicators of patients in Iran: a systematic review and meta-analysis.

BMC psychology
Spiritual health interventions have increasingly been recognized for their potential to improve general health outcomes. This study undertakes a systematic review and meta-analysis to evaluate their effectiveness on patient health in Iran. Data were ...

The Effectiveness and Feasibility of Conversational Agents in Supporting Care for Patients With Cancer: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Patients with cancer experience complex physical, psychosocial, and behavioral challenges that require continuous support. This need has intensified with the rising cancer burden worldwide and the limited scalability of traditional care m...

Unsupervised machine learning approach to interpret complex lower urinary tract symptoms and their impact on quality of life in adult women.

World journal of urology
PURPOSE: To identify clinically meaningful clusters of lower urinary tract symptoms (LUTS) in adult women using an unsupervised machine learning approach and to examine their associations with patient-centered outcomes, including quality of life (QoL...

AI-based prediction of depression symptomatology in first-episode psychosis patients: insights from the EUFEST and RAISE-ETP clinical trials.

Psychological medicine
BACKGROUND: Depressive symptoms are highly prevalent in first-episode psychosis (FEP) and worsen clinical outcomes. It is currently difficult to determine which patients will have persistent depressive symptoms based on a clinical assessment. We aime...

Does Humanness Matter? An Ethical Evaluation of Sharing Care Work with Social Robots.

Science and engineering ethics
While social robots offer potential benefits like task assistance and companionship, their integration raises concerns about the erosion of human connection and the dehumanization of care. Through a qualitative study of older adults, family caregiver...

Machine Learning Prediction of Financial Toxicity in Patients with Resected Lung Cancer.

Journal of the American College of Surgeons
BACKGROUND: Financial toxicity (FT) refers to the financial stress and detrimental impact on quality of life experienced by patients due to treatment cost. In patients with resected lung cancer (LC), we sought to identify those at risk of developing ...