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

Ethical Standards I01:25

Ethical Standards I

1000
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,...
1000
Legal Guidelines for Documentation01:06

Legal Guidelines for Documentation

1.5K
The legal guidelines for nursing documentation are essential for ensuring accurate, professional, and ethical recording of patient care. The guidelines are discussed here:
1.5K
Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

901
The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:
901
Purpose of Health Records I01:11

Purpose of Health Records I

1.4K
The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:
1.4K
Ethical Standards II01:23

Ethical Standards II

819
Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
Nurses are entrusted with upholding various ethical principles and standards. Nurses forge solid therapeutic relationships using trust, empathy, autonomy, confidentiality, and professional competence.
Confidentiality is crucial, embodying respect for individual privacy...
819
Purpose of Health Records II01:19

Purpose of Health Records II

1.0K
Health records serve various essential purposes in the healthcare system. Here are some key purposes:
1.0K

You might also read

Related Articles

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

Sort by
Same author

A Breast Cancer Image Classification Algorithm with 2c Multiclass Support Vector Machine.

Journal of healthcare engineering·2023
Same author

Error Concealment in the Density Field of a Spatiotemporal Image Sequence.

Computational intelligence and neuroscience·2022
Same author

AES Based White Box Cryptography in Digital Signature Verification.

Sensors (Basel, Switzerland)·2022
Same author

Cyber-Internet Security Framework to Conquer Energy-Related Attacks on the Internet of Things with Machine Learning Techniques.

Computational intelligence and neuroscience·2022
Same author

Classification of Skin Cancer Lesions Using Explainable Deep Learning.

Sensors (Basel, Switzerland)·2022
Same author

Detection of Malicious Cloud Bandwidth Consumption in Cloud Computing Using Machine Learning Techniques.

Computational intelligence and neuroscience·2022

Related Experiment Video

Updated: Sep 28, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.0K

Novel Method for Safeguarding Personal Health Record in Cloud Connection Using Deep Learning Models.

Sarvesh Kumar1, Mohammed Abdul Wajeed2, Rajashekhar Kunabeva3

  • 1Department of Computer Science and Engineering, BBD University, Lucknow, India.

Computational Intelligence and Neuroscience
|March 29, 2022
PubMed
Summary

This study introduces security measures for cloud-based personal health records (PHR) to protect patient data. An optimized rule-based fuzzy inference system (ORFIS) effectively predicts patient criticality, enhancing healthcare security and efficiency.

More Related Videos

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.4K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

Related Experiment Videos

Last Updated: Sep 28, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.0K
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.4K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

Area of Science:

  • Health Informatics
  • Cloud Computing Security
  • Artificial Intelligence in Healthcare

Background:

  • Managing patient health records (PHR) in the cloud offers cost savings for healthcare institutions.
  • Existing systems face challenges with unauthorized access, privacy, security, and query response times when using third-party servers.
  • Intelligent examination of PHRs can predict patient criticality within healthcare systems.

Purpose of the Study:

  • To present novel security measures for cloud-based personal health records (PHR).
  • To develop an optimized system for predicting patient criticality using PHR data.
  • To enhance data storage, retrieval efficiency, access granularity, and response time for PHRs in a private cloud.

Main Methods:

  • Implementation of an optimized rule-based fuzzy inference system (ORFIS) for patient criticality assessment.
  • Classification of patients into three severity groups: very critical, less critical, and normal.
  • Utilizing a graph-based access policy and anonymous authentication with a NoSQL database in a private cloud environment.

Main Results:

  • The proposed ORFIS demonstrated superior performance compared to existing fuzzy inference methods in detecting PHR criticality.
  • The implemented security solutions improved data storage and retrieval efficiency.
  • Enhanced granularity of data access and reduced response times were achieved.

Conclusions:

  • The developed security measures effectively address privacy, security, and access control for cloud-based PHRs.
  • ORFIS provides an accurate and efficient method for predicting patient criticality.
  • The combination of ORFIS, graph-based access policies, and anonymous authentication in a private cloud environment optimizes PHR management.