Personalized medicine with advanced analytics
H Wang, D Feng, Y Liu - Real-World Evidence in Medical Product …, 2023 - Springer
Practice of modern medicine demands personalized medicine (PM) to improve both quality
of care and efficiency of the healthcare system. This is especially true as continued …
of care and efficiency of the healthcare system. This is especially true as continued …
Imputation-based Q-learning for optimizing dynamic treatment regimes with right-censored survival outcome
Q-learning has been one of the most commonly used methods for optimizing dynamic
treatment regimes (DTRs) in multistage decision-making. Right-censored survival outcome …
treatment regimes (DTRs) in multistage decision-making. Right-censored survival outcome …
Stabilized direct learning for efficient estimation of individualized treatment rules
In recent years, the field of precision medicine has seen many advancements. Significant
focus has been placed on creating algorithms to estimate individualized treatment rules …
focus has been placed on creating algorithms to estimate individualized treatment rules …
Enhancing Medical Training through Learning from Mistakes by Interacting with an Ill-trained Reinforcement Learning Agent
This article presents a 3-D medical simulation that employs reinforcement learning (RL) and
interactive RL (IRL) to teach and assess the procedure of donning and doffing personal …
interactive RL (IRL) to teach and assess the procedure of donning and doffing personal …
Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival data
An individualized treatment regime (ITR) is a decision rule that assigns treatments based on
patients' characteristics. The value function of an ITR is the expected outcome in a …
patients' characteristics. The value function of an ITR is the expected outcome in a …
Estimation of optimal treatment regimes with electronic medical record data using the residual life value estimator
G Rhodes, M Davidian, W Lu - Biostatistics, 2024 - academic.oup.com
Clinicians and patients must make treatment decisions at a series of key decision points
throughout disease progression. A dynamic treatment regime is a set of sequential decision …
throughout disease progression. A dynamic treatment regime is a set of sequential decision …
On estimation of optimal dynamic treatment regimes with multiple treatments for survival data-with application to colorectal cancer study
Z Liu, Z Zhan, J Liu, D Yi, C Lin, Y Yang - arXiv preprint arXiv:2310.05049, 2023 - arxiv.org
Dynamic treatment regimes (DTR) are sequential decision rules corresponding to several
stages of intervention. Each rule maps patients' covariates to optional treatments. The …
stages of intervention. Each rule maps patients' covariates to optional treatments. The …
Relative sparsity for medical decision problems
SJ Weisenthal, SW Thurston, A Ertefaie - Statistics in Medicine, 2023 - Wiley Online Library
Existing statistical methods can estimate a policy, or a mapping from covariates to decisions,
which can then instruct decision makers (eg, whether to administer hypotension treatment …
which can then instruct decision makers (eg, whether to administer hypotension treatment …
Uncertainty quantification for intervals
Data following an interval structure are increasingly prevalent in many scientific applications.
In medicine, clinical events are often monitored between two clinical visits, making the exact …
In medicine, clinical events are often monitored between two clinical visits, making the exact …
[PDF][PDF] AI in Pharma for Personalized Sequential Decision-Making: Methods, Applications and Opportunities
In the pharmaceutical industry, the use of artificial intelligence (AI) has seen consistent
growth over the past decade. This rise is attributed to major advancements in statistical …
growth over the past decade. This rise is attributed to major advancements in statistical …