Reinforcement Machine Learning - AI Medical Compendium

Autonomous countertraction for secure field of view in laparoscopic surgery using deep reinforcement learning.

International journal of computer assisted radiology and surgery Sep 16, 2024

PURPOSE: Countertraction is a vital technique in laparoscopic surgery, stretching the tissue surface for incision and dissection. Due to the technical challenges and frequency of countertraction, autonomous countertraction has the potential to signif...

Laparoscopy Phantoms, Imaging Reinforcement Machine Learning Humans Neural Networks, Computer Computer Simulation Deep Learning

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Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management.

Computers in biology and medicine Jun 1, 2025

BACKGROUND: Managing blood glucose levels in Type 1 Diabetes Mellitus (T1DM) is essential to prevent complications. Traditional insulin delivery methods often require significant patient involvement, limiting automation. Reinforcement Learning (RL)-b...

Pancreas, Artificial Female Reinforcement Machine Learning Blood Glucose Adult Insulin Infusion Systems Humans Insulin Diabetes Mellitus, Type 1 Computer Simulation Male Hypoglycemic Agents Precision Medicine Deep Learning

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A Deep Reinforcement Learning Based Region-Specific Beamformer for Sparse Arrays 3-D Ultrasound Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Jun 1, 2025

Sparse arrays offer several advantages over other element reduction techniques for 3-D ultrasound imaging. However, the large interelement spacing in these arrays results in high sidelobe-related artifacts, which significantly degrade image quality a...

Deep Learning Ultrasonography Humans Algorithms Phantoms, Imaging Reinforcement Machine Learning Imaging, Three-Dimensional Artifacts

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Optimal Vasopressin Initiation in Septic Shock: The OVISS Reinforcement Learning Study.

JAMA May 20, 2025

IMPORTANCE: Norepinephrine is the first-line vasopressor for patients with septic shock. When and whether a second agent, such as vasopressin, should be added is unknown.

Humans Organ Dysfunction Scores Critical Illness Datasets as Topic Vasopressins Electronic Health Records Practice Guidelines as Topic Norepinephrine Reinforcement Machine Learning Vasoconstrictor Agents Middle Aged Aged Hospital Mortality Clinical Decision-Making Shock, Septic Male Observational Studies as Topic Female

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Enhanced intelligent train operation algorithms for metro train based on expert system and deep reinforcement learning.

PloS one Jan 1, 2025

In recent decades, automatic train operation (ATO) systems have been gradually adopted by many metro systems, primarily due to their cost-effectiveness and practicality. However, a critical examination reveals computational constraints, adaptability ...

Expert Systems Reinforcement, Psychology Algorithms Deep Learning Reinforcement Machine Learning Railroads Humans

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Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024

Blood pressure variability (BPV) plays a critical role in vascular diseases, particularly in acute ischemic stroke patients in intensive care units (ICUs), where higher BPV correlates with increased mortality rates. Current interventions lack effecti...

Humans Intensive Care Units Antihypertensive Agents Stroke Reinforcement Machine Learning Nicardipine Infusions, Intravenous Blood Pressure Deep Learning Hypertension

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AIMC Topic: Reinforcement Machine Learning

Autonomous countertraction for secure field of view in laparoscopic surgery using deep reinforcement learning.

Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management.

A Deep Reinforcement Learning Based Region-Specific Beamformer for Sparse Arrays 3-D Ultrasound Imaging.

Optimal Vasopressin Initiation in Septic Shock: The OVISS Reinforcement Learning Study.

Enhanced intelligent train operation algorithms for metro train based on expert system and deep reinforcement learning.

Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.

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AIMC Topic: Reinforcement Machine Learning

Autonomous countertraction for secure field of view in laparoscopic surgery using deep reinforcement learning.

Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management.

A Deep Reinforcement Learning Based Region-Specific Beamformer for Sparse Arrays 3-D Ultrasound Imaging.

Optimal Vasopressin Initiation in Septic Shock: The OVISS Reinforcement Learning Study.

Enhanced intelligent train operation algorithms for metro train based on expert system and deep reinforcement learning.

Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.

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