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Patient Acceptance of Health Care

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The help-seeking process and predictors of mental health care use among individuals with depressive symptoms: a machine learning approach.

Frontiers in public health
PURPOSE: The goal of the study was to identify the most important influences on professional healthcare use of people with depressive symptoms. We incorporated findings from research areas of health behaviors, stigma, and motivation to predict the he...

Exploring correlates of high psychiatric inpatient utilization in Switzerland: a descriptive and machine learning analysis.

BMC psychiatry
BACKGROUND: This study investigated socio-demographic, psychiatric, and psychological characteristics of patients with high versus low utilization of psychiatric inpatient services. Our objective was to better understand the utilization pattern and t...

Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia.

Journal of Alzheimer's disease : JAD
Digital health innovations hold diagnostic and therapeutic promise but may be subject to biases for underrepresented groups. We explored perceptions of using artificial intelligence (AI) diagnostics for dementia through a focus group as part of the A...

Exploring Older Adults' Perspectives and Acceptance of AI-Driven Health Technologies: Qualitative Study.

JMIR aging
BACKGROUND: Artificial intelligence (AI) is increasingly being applied in various health care services due to its enhanced efficiency and accuracy. As the population ages, AI-based health technologies could be a potent tool in older adults' health ca...

Trust and Acceptance Challenges in the Adoption of AI Applications in Health Care: Quantitative Survey Analysis.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) has potential to transform health care, but its successful implementation depends on the trust and acceptance of consumers and patients. Understanding the factors that influence attitudes toward AI is crucial ...

SEM model analysis of diabetic patients' acceptance of artificial intelligence for diabetic retinopathy.

BMC medical informatics and decision making
AIMS: This study aimed to investigate diabetic patients' acceptance of artificial intelligence (AI) devices for diabetic retinopathy screening and the related influencing factors.

Using Machine Learning to Predict Uptake to an Online Self-Guided Intervention for Stress During the COVID-19 Pandemic.

Stress and health : journal of the International Society for the Investigation of Stress
Online self-guided interventions appear efficacious for alleviating some mental health concerns. However, among persons who are offered online interventions, only a fraction access them (i.e., achieve uptake). Machine learning methods may be useful t...

Predicting Prostate Cancer Diagnosis Using Machine Learning Analysis of Healthcare Utilization Patterns.

Studies in health technology and informatics
This study investigated healthcare utilization patterns prior to prostate cancer diagnoses, aiming to develop machine learning models for early prediction of cancer diagnosis. Data from the All of Us Research Program was used, focusing on adult patie...

Acceptability, applicability, and cost-utility of artificial-intelligence-powered low-cost portable fundus camera for diabetic retinopathy screening in primary health care settings.

Diabetes research and clinical practice
AIMS: To evaluate the acceptability, applicability, and cost-utility of AI-powered portable fundus cameras for diabetic retinopathy (DR) screening in Hong Kong, providing a viable alternative screening solution for resource-limited areas.

Enhancing Patient Acceptance of Robotic Ultrasound through Conversational Virtual Agent and Immersive Visualizations.

IEEE transactions on visualization and computer graphics
Robotic ultrasound systems have the potential to improve medical diagnostics, but patient acceptance remains a key challenge. To address this, we propose a novel system that combines an AI-based virtual agent, powered by a large language model (LLM),...