AIMC Topic: Medication Adherence
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Breaking Barriers in Behavioral Change: The Potential of Artificial Intelligence-Driven Motivational Interviewing.
Journal of glaucoma
Apr 10, 2024
Patient outcomes in ophthalmology are greatly influenced by adherence and patient participation, which can be particularly challenging in diseases like glaucoma, where medication regimens can be complex. A well-studied and evidence-based intervention...
Exploring the Use of Socially Assistive Robots Among Socially Isolated Korean American Older Adults.
Journal of applied gerontology : the official journal of the Southern Gerontological Society
Feb 26, 2024
This pilot study explored whether a socially assistive robot (SAR) would have positive effects on Korean American immigrant older adults' health behaviors and emotional well-being and whether the older adults would be receptive to the SAR. A total of...
Developing an Artificial Intelligence-Driven Nudge Intervention to Improve Medication Adherence: A Human-Centred Design Approach.
Journal of medical systems
Dec 8, 2023
To improve medication adherence, we co-developed a digital, artificial intelligence (AI)-driven nudge intervention with stakeholders (patients, providers, and technologists). We used a human-centred design approach to incorporate user needs in creati...
Psychometric Properties of a Machine Learning-Based Patient-Reported Outcome Measure on Medication Adherence: Single-Center, Cross-Sectional, Observational Study.
Journal of medical Internet research
Oct 16, 2023
BACKGROUND: Medication adherence plays a critical role in controlling the evolution of chronic disease, as low medication adherence may lead to worse health outcomes, higher mortality, and morbidity. Assessment of their patients' medication adherence...
The use of digital health in heart rhythm care.
Expert review of cardiovascular therapy
Jun 23, 2023
INTRODUCTION: Digital health is a broad term that includes telecommunication technologies to collect, share and manipulate health information to improve patient health and health care services. With the growing use of wearables, artificial intelligen...
Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device.
BMC medical informatics and decision making
Jul 6, 2022
BACKGROUND: Our aim was to develop a machine learning model, using real-world data captured from a connected auto-injector device and from early indicators from the first 3 months of treatment, to predict sub-optimal adherence to recombinant human gr...
A machine-learning assisted review of the use of habit formation in medication adherence interventions for long-term conditions.
Health psychology review
Feb 14, 2022
Adherence to medication in long-term conditions is around 50%. The key components of successful interventions to improve medication adherence remain unclear, particularly when examined over prolonged follow-up periods. Behaviour change theories are i...
Machine learning models to identify low adherence to influenza vaccination among Korean adults with cardiovascular disease.
BMC cardiovascular disorders
Mar 9, 2021
BACKGROUND: Annual influenza vaccination is an important public health measure to prevent influenza infections and is strongly recommended for cardiovascular disease (CVD) patients, especially in the current coronavirus disease 2019 (COVID-19) pandem...
Accuracy of machine learning-based prediction of medication adherence in clinical research.
Psychiatry research
Nov 4, 2020
Medication non-adherence represents a significant barrier to treatment efficacy. Remote, real-time measurement of medication dosing can facilitate dynamic prediction of risk for medication non-adherence, which in-turn allows for proactive clinical in...
Deep CNN Sparse Coding for Real Time Inhaler Sounds Classification.
Sensors (Basel, Switzerland)
Apr 21, 2020
Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indicates, medication adherence can effectively be monitored by successfully identifying actions performe...
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