AIMC Topic: Patient Acceptance of Health Care
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Exploring Older Adults' Perspectives and Acceptance of AI-Driven Health Technologies: Qualitative Study.
JMIR aging
Feb 12, 2025
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...
Exploring correlates of high psychiatric inpatient utilization in Switzerland: a descriptive and machine learning analysis.
BMC psychiatry
Dec 23, 2024
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...
Feasibility and Acceptance of a Remotely Supervised Home-Based Group Mobility Exercise for Older Adults Using a Mobile Robotic Telepresence: A Pilot Study.
Journal of aging and physical activity
Dec 20, 2024
BACKGROUND/OBJECTIVES: Mobile robotic telepresence could be used to remotely supervise physical activity programs. Our study aims to explore the feasibility, acceptance, and usability of a physical activity program offered synchronously via a mobile...
The help-seeking process and predictors of mental health care use among individuals with depressive symptoms: a machine learning approach.
Frontiers in public health
Nov 20, 2024
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...
Acceptability of artificial intelligence in dental radiology among patients in India: are we ready for this revolution?
Oral radiology
Oct 9, 2024
OBJECTIVE: In recent times, artificial Intelligence (AI) has gained popularity in medical as well as dental radiology. Studies have been conducted among medical and dental students and professionals about the knowledge and understanding towards AI. T...
The acceptability and effectiveness of artificial intelligence-based chatbot for hypertensive patients in community: protocol for a mixed-methods study.
BMC public health
Aug 21, 2024
BACKGROUND: Chatbots can provide immediate assistance tailored to patients' needs, making them suitable for sustained accompanying interventions. Nevertheless, there is currently no evidence regarding their acceptability by hypertensive patients and ...
Predictive modeling for identification of older adults with high utilization of health and social services.
Scandinavian journal of primary health care
Jul 3, 2024
AIM: Machine learning techniques have demonstrated success in predictive modeling across various clinical cases. However, few studies have considered predicting the use of multisectoral health and social services among older adults. This research aim...
Acceptability of artificial intelligence for cervical cancer screening in Dschang, Cameroon: a qualitative study on patient perspectives.
Reproductive health
Jun 28, 2024
BACKGROUND: Cervical cancer is the fourth most frequent cancer among women, with 90% of cervical cancer-related deaths occurring in low- and middle-income countries like Cameroon. Visual inspection with acetic acid is often used in low-resource setti...
Machine learning algorithms to predict healthcare-seeking behaviors of mothers for acute respiratory infections and their determinants among children under five in sub-Saharan Africa.
Frontiers in public health
Jun 19, 2024
BACKGROUND: Acute respiratory infections (ARIs) are the leading cause of death in children under the age of 5 globally. Maternal healthcare-seeking behavior may help minimize mortality associated with ARIs since they make decisions about the kind and...
Exploring predictors of substance use disorder treatment engagement with machine learning: The impact of social determinants of health in the therapeutic landscape.
Journal of substance use and addiction treatment
Jun 8, 2024
BACKGROUND: Improved knowledge of factors that influence treatment engagement could help treatment providers and systems better engage patients. The present study used machine learning to explore associations between individual- and neighborhood-leve...
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