Latest AI and machine learning research in surveys for healthcare professionals.
In this article, an online reinforcement learning (RL) control method through value iteration (VI) is developed to solve the optimal cooperative control problem for the unknown linear discrete-time multiagent systems (MASs). On the one hand, an online learning scheme with evolving policies is proposed in order to guarantee the stability of the MASs under immature policies generated by VI. Inspired...
Pressure ulcers are a serious clinical problem associated with high morbidity, mortality and healthcare costs, especially in intensive care unit (ICU) patients. Existing risk assessment tools, such as the Braden Score, are often inadequate in ICU patients and have poor discriminatory power between classes. This increases the need for more sensitive, predictive and integrative systems. The aim of ...
Ethical dilemmas exist with decision-making regarding resource allocations, such as critical care, ventilators and other critical equipment, and pharm...
Natural disasters, including earthquakes, wildfires and cyclones, bear a huge risk on human lives as well as infrastructure assets. An effective res...
OBJECTIVES: Administrative data are commonly used to inform chronic disease prevalence and support health informatic research. This study assessed the...
This article describes the staged restructure of the rapid response program into a dedicated 24/7 proactive rapid response system in a quaternary acad...
Evaluating generative models for synthetic medical imaging is crucial yet challenging, especially given the high standards of fidelity, anatomical a...
Segmentation of the airway tree plays a vital role in clinical practice. However, the complex airway tree structure makes it quite challenging to anno...
Pharmacology is a cornerstone of pharmacy education, bridging biomedical sciences with clinical application. Understanding students' perceptions of ph...
Structural Health Monitoring (SHM) relies on the effective communication between sensors and diagnostic systems, yet data interpretation remains incon...
This paper discusses ethics-based strategies for mitigating bias in machine learning models used to predict sepsis onset. The first part discusses how...
The Society of Thoracic Radiology (STR) membership enthusiastically embraced the launch of its mentorship program, with peaks in participation and eng...
What does Artificial Intelligence (AI) have to contribute to health care? And what should we be looking out for if we are worried about its risks? I...
Achieving group-robust generalization in the presence of spurious correlations remains a significant challenge, particularly when bias annotations a...
This systematic review aims to assess the effectiveness of AI-Driven Decision Support Systems in improving glycemic control, measured by Time in Range...
Integrating artificial intelligence, particularly large language models (LLMs), into medical education represents a significant new step in how medica...
Text-to-image person search aims to identify an individual based on a text description. To reduce data collection costs, large-scale text-image data...
To systematically review the progress in the method development and application of distributed learning in the estimation of epidemiological effect a...
Although machine learning is frequently used in medicine for predictive purposes, its accuracy in diabetes-related amputation (DRA) remains unclear. F...
Ultra-wideband (UWB) technology has shown remarkable potential as a low-cost general solution for robot localization. However, limitations of the UW...