Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions
HH Rashidi, KA Bowers, MR Gil - Journal of Thrombosis and Haemostasis, 2022 - Elsevier
Artificial Intelligence (AI) and machine learning (ML) studies are increasingly populating the
life science space and some have also started to integrate certain clinical decision support …
life science space and some have also started to integrate certain clinical decision support …
[HTML][HTML] Making machine learning matter to clinicians: model actionability in medical decision-making
Abstract Machine learning (ML) has the potential to transform patient care and outcomes.
However, there are important differences between measuring the performance of ML models …
However, there are important differences between measuring the performance of ML models …
A model-based hybrid soft actor-critic deep reinforcement learning algorithm for optimal ventilator settings
A ventilator is a device that mechanically assists in pumping air into the lungs, which is a life-
saving supportive therapy in an intensive care unit (ICU). In clinical scenarios, each patient …
saving supportive therapy in an intensive care unit (ICU). In clinical scenarios, each patient …
Network data acquisition and monitoring system for intensive care mechanical ventilation treatment
The rise of model-based and machine learning methods have created increasingly realistic
opportunities to implement personalized, patient-specific mechanical ventilation (MV) in the …
opportunities to implement personalized, patient-specific mechanical ventilation (MV) in the …
Optimization of dry weight assessment in hemodialysis patients via reinforcement learning
Z Yang, Y Tian, T Zhou, Y Zhu, P Zhang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Dry weight (DW), defined as the lowest tolerated postdialysis weight following the
ultrafiltration (UF) of excess fluid volume, is essential for any dialysis prescription for …
ultrafiltration (UF) of excess fluid volume, is essential for any dialysis prescription for …
Towards safe mechanical ventilation treatment using deep offline reinforcement learning
Mechanical ventilation is a key form of life support for patients with pulmonary impairment.
Healthcare workers are required to continuously adjust ventilator settings for each patient, a …
Healthcare workers are required to continuously adjust ventilator settings for each patient, a …
[HTML][HTML] Artificial intelligence in perioperative medicine: a narrative review
Recent advancements in artificial intelligence (AI) techniques have enabled the
development of accurate prediction models using clinical big data. AI models for …
development of accurate prediction models using clinical big data. AI models for …
[HTML][HTML] Artificial intelligence for clinical decision support for monitoring patients in cardiovascular ICUs: A systematic review
Background: Artificial intelligence (AI) and Machine Learning (ML) models continue to
evolve the clinical decision support systems (CDSS). However, challenges arise when it …
evolve the clinical decision support systems (CDSS). However, challenges arise when it …
Towards robust off-policy evaluation via human inputs
Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes
domains such as healthcare, where direct deployment is often infeasible, unethical, or …
domains such as healthcare, where direct deployment is often infeasible, unethical, or …
[HTML][HTML] Development and validation of a reinforcement learning model for ventilation control during emergence from general anesthesia
Ventilation should be assisted without asynchrony or cardiorespiratory instability during
anesthesia emergence until sufficient spontaneous ventilation is recovered. In this …
anesthesia emergence until sufficient spontaneous ventilation is recovered. In this …