AIMC Topic: Patient Compliance

Clear Filters Showing 21 to 30 of 41 articles

Comparative analysis of predictive methods for early assessment of compliance with continuous positive airway pressure therapy.

BMC medical informatics and decision making
BACKGROUND: Patients suffering obstructive sleep apnea are mainly treated with continuous positive airway pressure (CPAP). Although it is a highly effective treatment, compliance with this therapy is problematic to achieve with serious consequences f...

Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch.

Physiological measurement
OBJECTIVE: Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common shoulder disorders. However, adherence to these protocols is often poor and typically worse for unsupe...

Using machine-learning approaches to predict non-participation in a nationwide general health check-up scheme.

Computer methods and programs in biomedicine
BACKGROUND: In the time since the launch of a nationwide general health check-up and instruction program in Japan in 2008, interest in the formulation of an effective and efficient strategy to improve the participation rate has been growing. The aim ...

Application of Machine Learning to Predict Dietary Lapses During Weight Loss.

Journal of diabetes science and technology
BACKGROUND: Individuals who adhere to dietary guidelines provided during weight loss interventions tend to be more successful with weight control. Any deviation from dietary guidelines can be referred to as a "lapse." There is a growing body of resea...

Is Treatment Readiness Associated With Substance Use Treatment Engagement? An Exploratory Study.

Journal of drug education
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
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
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
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
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
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.