Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

911
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
911
Ethical Standards I01:25

Ethical Standards I

959
The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
959
Integrated Healthcare System01:20

Integrated Healthcare System

1.8K
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
1.8K
Nursing Clinical Information System01:27

Nursing Clinical Information System

860
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
860
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.8K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.8K
Data Validation01:03

Data Validation

5.3K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
5.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Structural, optical, dielectric, and quantum-chemical investigation of glycine phosphite nanocrystals for optoelectronic application.

Journal of molecular modeling·2025
Same author

One-pot synthesis of g-C<sub>3</sub>N<sub>4</sub>/N-doped CeO<sub>2</sub> nanocomposites and their potential visible light-driven photocatalytic degradation of methylene blue dye.

Environmental geochemistry and health·2024
Same author

Smart Contract Authentication assisted GraphMap-Based HL7 FHIR architecture for interoperable e-healthcare system.

Heliyon·2023
Same author

Characterization of a novel natural cellulosic fiber from Calotropis gigantea fruit bunch for ecofriendly polymer composites.

International journal of biological macromolecules·2020
Same author

Ursolic acid modulates MMPs, collagen-I, α-SMA, and TGF-β expression in isoproterenol-induced myocardial infarction in rats.

Human & experimental toxicology·2019
Same author

Structural and functional assessment of macula to diagnose glaucoma.

Eye (London, England)·2016
Same journal

Evaluating a Novel Cell-Free Preservation Solution for Human Cardiomyocyte Protection: A Proof-of-Concept Study.

BioMed research international·2026
Same journal

Clinical Efficacy of Chinese Medicine in Treating Adult Henoch-Schönlein Purpura: A Meta-Analysis.

BioMed research international·2026
Same journal

RETRACTION: Rehabilitation Training and Resveratrol Improve the Recovery of Neurological and Motor Function in Rats after Cerebral Ischemic Injury through the Sirt1 Signaling Pathway.

BioMed research international·2026
Same journal

The Oncogenic and Tumor-Suppressive Roles of SNHG18: A Double-Edged Long Noncoding RNA in Cancer.

BioMed research international·2026
Same journal

Evaluation of LncRNA NEAT1 and MEG3 Expression Levels in Hospitalized COVID-19 Patients.

BioMed research international·2026
Same journal

Perceived Self-Efficacy and Its Determinants for Noncommunicable Disease Prevention Among Adults in Southern Ethiopia: A Community-Based Cross-Sectional Study.

BioMed research international·2026
See all related articles

Related Experiment Video

Updated: Sep 7, 2025

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

9.4K

Dynamic Data Infrastructure Security for Interoperable e-Healthcare Systems: A Semantic Feature-Driven NoSQL

R Sreejith1, S Senthil2

  • 1School of Computing and Information Technology, REVA University, Bangalore, India.

Biomed Research International
|June 20, 2022
PubMed
Summary
This summary is machine-generated.

A novel model effectively detects NoSQL intrusion attacks in the Internet of Medical Things (IoMT) e-Healthcare systems. It achieves high accuracy using semantic features, feature selection, and a random forest classifier for robust database security.

More Related Videos

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.4K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.2K

Related Experiment Videos

Last Updated: Sep 7, 2025

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

9.4K
Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.4K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.2K

Area of Science:

  • Computer Science
  • Cybersecurity
  • Health Informatics

Background:

  • The Internet of Medical Things (IoMT) and interoperable e-Healthcare systems face significant database security challenges due to their heterogeneous and dynamic nature.
  • Classical databases are vulnerable to intrusion attacks like bot-attacks and malware, and even NoSQL databases struggle with dynamic data in complex environments.
  • Ensuring the security of electronic healthcare records (EHRs) and telemedicine platforms is critical for patient data protection.

Purpose of the Study:

  • To propose a novel semantic feature-driven NoSQL intrusion attack (NoSQL-IA) detection model specifically for interoperable e-Healthcare systems.
  • To evaluate various semantic feature extraction, feature selection, and resampling techniques for optimizing intrusion detection.
  • To identify the most effective machine learning classifier for accurately identifying NoSQL-IA in e-Healthcare databases.

Main Methods:

  • Assessed semantic feature extraction methods (Word2Vec, CBOW, SKG, Count Vectorizer, TF-IDF, GLOVE) for NoSQL-IA prediction.
  • Employed feature selection algorithms (WRST, Select K-Best, PCA, VTFS) to reduce computational load and improve efficiency.
  • Utilized resampling techniques (upsampling, downsampling, SMOTE) to address data imbalance, followed by Min-Max normalization and evaluation with multiple ML classifiers (Random Forest, XGBoost, etc.).

Main Results:

  • The combination of Word2Vec features with N-Skip Gram (SKG), Variance Threshold Feature Selection (VTFS), SMOTE resampling, and a bootstrapped Random Forest classifier yielded the highest performance.
  • Achieved exceptional results with 98.86% accuracy, 0.974 F-Measure, and 0.981 Area Under the Curve (AUC).
  • This integrated approach demonstrated superior capability in distinguishing regular queries from NoSQL-IA attack queries.

Conclusions:

  • The proposed semantic feature-driven NoSQL-IA detection model is highly effective for securing interoperable e-Healthcare databases.
  • The optimal configuration (Word2Vec-SKG, VTFS, SMOTE, Random Forest) provides a robust solution against sophisticated intrusion attacks.
  • This research contributes a significant advancement in protecting sensitive health data within the evolving IoMT landscape.