Correction: A Machine Learning Model to Predict Patients' Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial.

[This corrects the article DOI: 10.2196/48852.].

A Machine Learning Model to Predict Patients' Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial.

Background: Adherence to oral anticancer treatments is critical in the disease trajectory of patients with breast cancer. Given the impact of nonadherence on clinical outcomes and the associated economic burden for the health care system, finding ways to increase treatment adherence is particularly relevant.

Objective: The primary end point is to evaluate the effectiveness of a decision support system (DSS) and a machine learning web application in promoting adherence to oral anticancer treatments among patients with metastatic breast cancer.

"Interventions to increase adherence to oral therapies in breast cancer patients: A systematic review based on the behavior change technique taxonomy".

Objective: High rates of non-adherence to oral medications in breast cancer (BC) patients have been reported. Here we provide an up-to-date systematic review of the interventions aimed at increasing adherence to oral medication in BC patients, with a particular focus on the content of the interventions.

Methods: PubMed, Scopus, Embase and Ovid databases and reference lists of relevant studies were searched through October 2022.