… training machine learning methods to estimate individualized … ‐of‐the‐art machine learning
methods for causal inference, … and machine learning for making individualized treatment …

… ML is a powerful tool that can provide individualized patient risk profiles by more … ML
algorithms trained on readily available perioperative clinical data can provide an individualized risk …

… treatment rule based on an ensemble machine learning … suggest that a clinically useful
individualized treatment rule for … , 38 we used diverse candidate algorithms to optimize Super …

The individualized treatment recommendation (ITR) is an important analytic framework for …
From the machine learning perspective, the solution to the ITR problem can be formulated as …

… Patient factors can be used by the algorithm to provide predicted individualized scores of
future functional status after the initial insult. Using these predictions, which are based on a …

… to individualize … algorithm for a response to methotrexate based on sociodemographic,
clinical, serologic, and genomic data from patients with early RA using machine learning (ML) …

… machine learning approach based on matching (M-learning) to estimate optimal ITRs
from EHRs. This new learning … matching algorithm are available to be implemented in M-learning. …

… , an individualized treatment should be initiated. Using a combination of machine learning
… CDSS that automatically composes an individualized treatment that balances effectiveness, …

… , or pattern recognition, refers to an algorithm that is able to … of prediction models based on
machine learning. They provide well-… the potential of machine learning for individual outcome …

… algorithm contains different models for each stage. For the first stage, we developed different
fine-tuned Machine Learning (… Our algorithm was compared to a baseline VM consolidation …