Abstract
Background/Objectives: Interoperability among the hospitals is the major challenge in development and deployment of the clinical reporting system.In this paper, we demonstrate a HL7 (Health Level) FHIR (Fast Healthcare Interoperability Resources) standard to provide the interoperability among the healthcare information system.
Method/Statistical Analysis: FHIR (pronounced ”fire”), is successor of the HL7 v3 standard. FHIR can utilize the light weight devices and is based on REST architectural. Model integrated with the EHR (electronic health record) that store Mongo DB database and reports is generated through FHIR resources. Various authentic individuals like physician, staff, patient and family members of patient can access and update the report. On the basis of the report, the model can provide the prediction of the disease.
Findings: In our study, we examined dataset PIDD (Pima Indian Diabetes dataset) for the model. Dataset trained offline using the predictive techniques SVM, Naive Bayes and K-NN. Performance analysis was performed on the basis of response time and waiting time of a request.
Application/Improvements: Open source standard, technologies like FHIR and MONGO DB can play a prominent role in healthcare system and in the area of clinical research. Integrating the EHR with web services assists the physician for making the correct decision at right time.
Keywords: Fast Healthcare Interoperability Resources (FHIR), EHR (Electronic Health Record), K-NN, SVM techniques, Public data set, RESTful.
Graphical Abstract
Call for Papers in Thematic Issues
Federated learning for biomedical applications
Federated learning, also known as distributed AI/machine learning, is a method that enables cooperative learning from big datasets owned by several parties without compromising the privacy of each person's raw data. FL is especially helpful when the needed information is not open source or easily accessible due to tactical or ...read more
Information, Trust, and Risk: Exploring the Intersection of Sensing, Wireless Communications, and Control
Sensing technologies, wireless communications, and control systems are becoming ubiquitous in our daily lives, with the potential to enhance and streamline many aspects of modern society. However, this also creates new challenges in terms of ensuring trust and managing risks associated with the use of these technologies. The sheer volume ...read more
Machine Learning for Industry 4.0 manufacturing applications
This thematic issue will focus on the intersection of Machine Learning and the manufacturing industry within the context of Industry 4.0. Industry 4.0 involves the use of smart sensors, devices, and machines to enable the creation of smart factories that constantly collect data related to production. Machine Learning techniques can ...read more
Next-Generation Network Architecture, Algorithms, and Security
Design of new network architectures, algorithms and protocols is one of the fundamental challenges in next-generation networking. To this end, novel networking techniques and applications are required for advancing today?s complex communication networks. This thematic issue provides researchers, industry professionals and practitioners with a forum to present the latest research ...read more
Related Books
IoT-enabled Sensor Networks: Architecture, Methodologies, Security, and Futuristic Applications
AIoT and Big Data Analytics for Smart Healthcare Applications
Research Trends in Artificial Intelligence: Internet of Things
Artificial Intelligence and Multimedia Data Engineering
Basics of Python Programming: A Quick Guide for Beginners
Blockchain Technology in Healthcare - Concepts, Methodologies, and Applications
Artificial Intelligence and Knowledge Processing: Methods and Applications
Handbook of Artificial Intelligence
Amazon Web Services: the Definitive Guide for Beginners and Advanced Users
The Role of AI in Enhancing IoT-Cloud Applications
13
3