AIMC Topic: Assessment of Medication Adherence
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Identifying the Relative Importance of Factors Influencing Medication Compliance in General Patients Using Regularized Logistic Regression and LightGBM: Web-Based Survey Analysis.
JMIR formative research
Dec 23, 2024
BACKGROUND: Medication compliance, which refers to the extent to which patients correctly adhere to prescribed regimens, is influenced by various psychological, behavioral, and demographic factors. When analyzing these factors, challenges such as mul...
Imatinib adherence prediction using machine learning approach in patients with gastrointestinal stromal tumor.
Cancer
Sep 6, 2024
BACKGROUND: Nonadherence to imatinib is common in patients with gastrointestinal stromal tumor (GIST), which is associated with poor prognosis and financial burden. The primary aim of this study was to investigate the adherence rate in patients with ...
Self-help groups and opioid use disorder treatment: An investigation using a machine learning-assisted robust causal inference framework.
International journal of medical informatics
Jun 24, 2024
OBJECTIVES: This study investigates the impact of participation in self-help groups on treatment completion among individuals undergoing medication for opioid use disorder (MOUD) treatment. Given the suboptimal adherence and retention rates for MOUD,...
Opioid Nonadherence Risk Prediction of Patients with Cancer-Related Pain Based on Five Machine Learning Algorithms.
Pain research & management
Jun 6, 2024
OBJECTIVES: Opioid nonadherence represents a significant barrier to cancer pain treatment efficacy. However, there is currently no effective prediction method for opioid adherence in patients with cancer pain. We aimed to develop and validate a machi...
Predicting medication adherence using ensemble learning and deep learning models with large scale healthcare data.
Scientific reports
Sep 23, 2021
Clinical studies from WHO have demonstrated that only 50-70% of patients adhere properly to prescribed drug therapy. Such adherence failure can impact therapeutic efficacy for the patients in question and compromises data quality around the populatio...
Digital technologies to improve the precision of paediatric growth disorder diagnosis and management.
Growth hormone & IGF research : official journal of the Growth Hormone Research Society and the International IGF Research Society
Jun 4, 2021
Paediatric disorders of impaired linear growth are challenging to manage, in part because of delays in the identification of pathological short stature and subsequent referral and diagnosis, the requirement for long-term therapy, and frequent poor ad...
Random forest machine learning algorithm predicts virologic outcomes among HIV infected adults in Lausanne, Switzerland using electronically monitored combined antiretroviral treatment adherence.
AIDS care
Apr 8, 2020
Machine Learning (ML) can improve the analysis of complex and interrelated factors that place adherent people at risk of viral rebound. Our aim was to build ML model to predict RNA viral rebound from medication adherence and clinical data. Patients w...
Predicting treatment outcome of drug-susceptible tuberculosis patients using machine-learning models.
Informatics for health & social care
Feb 20, 2018
Tuberculosis (TB) is a deadly contagious disease and a serious global health problem. It is curable but due to its lengthy treatment process, a patient is likely to leave the treatment incomplete, leading to a more lethal, drug resistant form of dise...
An Imbalanced Learning based MDR-TB Early Warning System.
Journal of medical systems
May 21, 2016
As a man-made disease, multidrug-resistant tuberculosis (MDR-TB) is mainly caused by improper treatment programs and poor patient supervision, most of which could be prevented. According to the daily treatment and inspection records of tuberculosis (...
A deep learning-based medication behavior monitoring system.
Mathematical biosciences and engineering : MBE
Jan 28, 2021
The internet of things (IoT) and deep learning are emerging technologies in diverse research fields, including the provision of IT services in medical domains. In the COVID-19 era, intelligent medication behavior monitoring systems for stable patient...
Humans
Neural Networks, Computer
Software
Pandemics
SARS-CoV-2
Deep Learning
Biomedical Engineering
Assessment of Medication Adherence
Wearable Electronic Devices
Monitoring, Physiologic
Directly Observed Therapy
Computer Systems
Equipment Design
Medication Adherence
COVID-19 Drug Treatment
Internet of Things
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