AIMC Topic: Patient Compliance
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Is Treatment Readiness Associated With Substance Use Treatment Engagement? An Exploratory Study.
Journal of drug education
Feb 27, 2018
With nearly 8.2% of Americans experiencing substance use disorders (SUDs), a need exists for effective SUD treatment and for strategies to assist treatment participants to complete treatment programs (Chandler, Fletcher, & Volkow, 2009). The purpose ...
Depression and alcohol use disorder at antiretroviral therapy initiation led to disengagement from care in South Africa.
PloS one
Dec 27, 2017
We sought to assess mental health at the time of antiretroviral therapy (ART) initiation and subsequent retention in care over a six-month follow-up period. A total of 136 people living with HIV in South Africa were administered surveys measuring dem...
Text mining electronic hospital records to automatically classify admissions against disease: Measuring the impact of linking data sources.
Journal of biomedical informatics
Oct 11, 2016
OBJECTIVE: Text and data mining play an important role in obtaining insights from Health and Hospital Information Systems. This paper presents a text mining system for detecting admissions marked as positive for several diseases: Lung Cancer, Breast ...
A Context-Aware Application to Increase Elderly Users Compliance with Physical Rehabilitation Exercises at Home via Animatronic Biofeedback.
Journal of medical systems
Aug 30, 2015
Biofeedback from physical rehabilitation exercises has proved to lead to faster recovery, better outcomes, and increased patient motivation. In addition, it allows the physical rehabilitation processes carried out at the clinic to be complemented wit...
The use of artificial neural networks to predict delayed discharge and readmission in enhanced recovery following laparoscopic colorectal cancer surgery.
Techniques in coloproctology
Jun 19, 2015
BACKGROUND: Artificial neural networks (ANNs) can be used to develop predictive tools to enable the clinical decision-making process. This study aimed to investigate the use of an ANN in predicting the outcomes from enhanced recovery after colorectal...
BEAMER: A Data Informed Model to Improve Adherence Behaviour.
Studies in health technology and informatics
Jul 24, 2024
OBJECTIVE: In this poster, we will present the BEAMER model, an emerging disease-agnostic model to improve adherence behaviour based on actionable factors and promote optimal health outcomes for all.
Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare.
Journal of the American Medical Informatics Association : JAMIA
Feb 16, 2024
OBJECTIVE: The complexity and rapid pace of development of algorithmic technologies pose challenges for their regulation and oversight in healthcare settings. We sought to improve our institution's approach to evaluation and governance of algorithmic...
Comparative study of ChatGPT and human evaluators on the assessment of medical literature according to recognised reporting standards.
BMJ health & care informatics
Oct 1, 2023
INTRODUCTION: Amid clinicians' challenges in staying updated with medical research, artificial intelligence (AI) tools like the large language model (LLM) ChatGPT could automate appraisal of research quality, saving time and reducing bias. This study...
Using Deep Learning for Individual-Level Predictions of Adherence with Growth Hormone Therapy.
Studies in health technology and informatics
May 27, 2021
The problem of consistent therapy adherence is a current challenge for health informatics, and its solution can increase the success rate of treatments. Here we show a methodology to predict, at individual-level, future therapy adherence for patients...
Development of a predictive model for retention in HIV care using natural language processing of clinical notes.
Journal of the American Medical Informatics Association : JAMIA
Jan 15, 2021
OBJECTIVE: Adherence to a treatment plan from HIV-positive patients is necessary to decrease their mortality and improve their quality of life, however some patients display poor appointment adherence and become lost to follow-up (LTFU). We applied n...
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