An agent based architecture for high-risk neonate management at neonatal intensive care unit
Journal Title: Electronic Physician - Year 2018, Vol 10, Issue 1
Abstract
BACKGROUND: In recent years, the use of new tools and technologies has decreased the neonatal mortality rate. Despite the positive effect of using these technologies, the decisions are complex and uncertain in critical conditions when the neonate is preterm or has a low birth weight or malformations. There is a need to automate the high-risk neonate management process by creating real-time and more precise decision support tools. OBJECTIVE: To create a collaborative and real-time environment to manage neonates with critical conditions at the NICU (Neonatal Intensive Care Unit) and to overcome high-risk neonate management weaknesses by applying a multi agent based analysis and design methodology as a new solution for NICU management. METHODS: This study was a basic research for medical informatics method development that was carried out in 2017. The requirement analysis was done by reviewing articles on NICU Decision Support Systems. PubMed, Science Direct, and IEEE databases were searched. Only English articles published after 1990 were included; also, a needs assessment was done by reviewing the extracted features and current processes at the NICU environment where the research was conducted. We analyzed the requirements and identified the main system roles (agents) and interactions by a comparative study of existing NICU decision support systems. The Universal Multi Agent Platform (UMAP) was applied to implement a prototype of our multi agent based high-risk neonate management architecture. RESULTS: Local environment agents interacted inside a container and each container interacted with external resources, including other NICU systems and consultation centers. In the NICU container, the main identified agents were reception, monitoring, NICU registry, and outcome prediction, which interacted with human agents including nurses and physicians. CONCLUSION: Managing patients at the NICU units requires online data collection, real-time collaboration, and management of many components. Multi agent systems are applied as a well-known solution for management, coordination, modeling, and control of NICU processes. We are currently working on an outcome prediction module using artificial intelligence techniques for neonatal mortality risk prediction. The full implementation of the proposed architecture and evaluation is considered the future work
Authors and Affiliations
Jaleh Shoshtarian Malak, Reza Safdari, Hojjat Zeraati, Fatemeh Sadat Nayeri, Niloofar Mohammadzadeh, Seide Sedighe Seied Farajollah
Keywords
Related Articles
- EP ID EP337591
- DOI 10.19082/6193
- Views 85
- Downloads 0
Diacerein: A potential therapeutic drug for the management of experimental periodontitis in rats.
Knowledge about the pathogenic process in the progression of periodontal disease indicates that the central cause of periodontal disease is the loss of a healthy balance between microbial virulence factors and the host's...
Evaluation of serum Resistin in children with chronic renal failure undergoing hemodialysis
INTRODUCTION: High serum resistin levels are associated with the incidence of chronic kidney disease (CKD). The objectives of this study were to determine the serum concentrations of resistin in children that present wit...
Role of alteration in Treg/Th17 cells' balance in nephropathic patients with Type 2 diabetes mellitus.
In type 2 diabetes mellitus, the adaptive immune system drives systemic inflammation, promoting insulin resistance and related complications, such as diabetic nephropathy. Increased infiltration of activated T lymphocyte...
Laparoscopic Repair of Perforated Peptic Ulcer: Outcome and Associated Morbidity and Mortality
INTRODUCTION: The mainstay of treatment for perforated peptic ulcer is Omental patch closure. With the advent of laparoscopic surgery, this approach is being used for the treatment of perforated peptic ulcer. The aim of...
Awareness, knowledge, and attitude of dentistry students in Kerman towards evidence-based dentistry
INTRODUCTION: Evidence-based care helps dentists provide quality dental services to patients, and such care is based on the use of reliable information about treatment and patient care from a large number of papers, book...