Dai-net: Dual adaptive interaction network for coordinated medication recommendation
Medication recommendation is a productive task for AI-driven healthcare systems, which can
assist clinicians in prescribing judicious and effective treatments. However, existing …
assist clinicians in prescribing judicious and effective treatments. However, existing …
Towards optimization and model selection for domain generalization: A mixup-guided solution
The distribution shifts between training and test data typically undermine the performance of
deep learning models. In recent years, lots of work pays attention to domain generaliza-tion …
deep learning models. In recent years, lots of work pays attention to domain generaliza-tion …
Reinforcement learning model for optimizing dexmedetomidine dosing to prevent delirium in critically ill patients
Delirium can result in undesirable outcomes including increased length of stays and
mortality in patients admitted to the intensive care unit (ICU). Dexmedetomidine has …
mortality in patients admitted to the intensive care unit (ICU). Dexmedetomidine has …
A drug mix and dose decision algorithm for individualized type 2 diabetes management
Pharmacotherapy guidelines for type 2 diabetes (T2D) emphasize patient-centered care, but
applying this approach effectively in outpatient practice remains challenging. Data-driven …
applying this approach effectively in outpatient practice remains challenging. Data-driven …
Position: reinforcement learning in dynamic treatment regimes needs critical reexamination
In the rapidly changing healthcare landscape, the implementation of offline reinforcement
learning (RL) in dynamic treatment regimes (DTRs) presents a mix of unprecedented …
learning (RL) in dynamic treatment regimes (DTRs) presents a mix of unprecedented …
A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning
Patients with type 1 diabetes and their physicians have long desired a fully closed-loop
artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation …
artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation …
Intelligent Dual Basal–Bolus Calculator for Multiple Daily Insulin Injections Via Offline Reinforcement Learning
Managing blood glucose levels through multiple daily injections (MDIs) of insulin presents a
challenge in daily diabetes care, necessitating frequent self-dosing adjustments to avoid …
challenge in daily diabetes care, necessitating frequent self-dosing adjustments to avoid …
[HTML][HTML] Smart pain relief: Harnessing conservative Q learning for personalized and dynamic pain management
Pain represents a multifaceted sensory and emotional experience often linked to tissue
damage, bearing substantial healthcare costs and profound effects on patient well-being …
damage, bearing substantial healthcare costs and profound effects on patient well-being …
Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
In the rapidly changing healthcare landscape, the implementation of offline reinforcement
learning (RL) in dynamic treatment regimes (DTRs) presents a mix of unprecedented …
learning (RL) in dynamic treatment regimes (DTRs) presents a mix of unprecedented …
TrajDeleter: Enabling Trajectory Forgetting in Offline Reinforcement Learning Agents
Reinforcement learning (RL) trains an agent from experiences interacting with the
environment. In scenarios where online interactions are impractical, offline RL, which trains …
environment. In scenarios where online interactions are impractical, offline RL, which trains …