Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

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...

Integrated Healthcare System

Integrated Healthcare System

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,...

Health Information Technology and Healthcare Information System

Health Information Technology and Healthcare Information System

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

Secondary Healthcare System

Secondary Healthcare System

Secondary healthcare is offered by a specialist, generally in hospitals or clinics for patients referred by primary healthcare providers. It occurs when a person has an illness or injury that requires specific medical care. Secondary care is often referred to as acute care. Secondary care can range from uncomplicated care to repair a minor laceration or treat a strep throat infection to more complicated emergent care, such as treating a head injury sustained in an automobile accident. Whatever...

Purpose of Health Records II

Purpose of Health Records II

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

Purpose of Health Records I

Purpose of Health Records I

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:

You might also read

Related Articles

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

Sort by

Same author

Multimodal machine learning and deep graph neural networks for the prediction of molecular inhibitory activity and disease associations.

Journal of computer-aided molecular design·2026

Same author

IDMBD: Intelligent Diagnostic Modelling of Bipolar Disorder at its early onset.

Scientific reports·2026

Same author

Geometric deep reinforcement learning with hierarchical variational autoencoders for de novo drug design and activity optimization.

Journal of computer-aided molecular design·2026

Same author

MedLedgerFL: a hybrid blockchain-federated learning framework for secure remote healthcare services.

Scientific reports·2026

Same author

MedShieldFL-a privacy-preserving hybrid federated learning framework for intelligent healthcare systems.

Scientific reports·2025

Same author

ChainShieldML an intelligent decentralized security framework for next generation wireless sensor networks.

Scientific reports·2025

Search research articles

Related Experiment Videos

A fuzzy logic and blockchain-enhanced framework for secure, explainable eHealth in Society 5.0.

Dileep Kumar Murala¹, Kumar Babu Batta², K Madhura³

¹Department of Computer Science and Engineering, Faculty of Science and Technology (ICFAI Tech), ICFAI Foundation for Higher Education, Hyderabad, Telangana, 501203, India.

Scientific Reports

|May 13, 2026

Summary

This study introduces a new framework for intelligent healthcare systems, integrating edge computing and blockchain for secure, real-time health predictions. It enhances patient trust through explainable AI, overcoming limitations of current cloud-based approaches.

Keywords:

Blockchain Edge computing Explainable AI (XAI)Fuzzy logic Health prediction IoMT (internet of medical things)PoAh 2.0 Society 5.0 eHealth

Related Experiment Videos

Area of Science:

Intelligent Healthcare Systems
Society 5.0
Explainable Artificial Intelligence (XAI)

Background:

Current intelligent healthcare systems face challenges like cloud system delays, single points of failure, and data privacy concerns.
Traditional AI models in healthcare often lack transparency and explainability, hindering physician trust and patient acceptance.
Existing systems struggle with real-time data processing from the Internet of Medical Things (IoMT).

Purpose of the Study:

To propose a novel framework for expanding eHealth within the Society 5.0 paradigm.
To address limitations of centralized cloud systems and black-box AI models in healthcare.
To enhance the security, privacy, responsiveness, and interpretability of intelligent healthcare systems.

Main Methods:

A multi-tiered architecture combining cloud services, edge computing, and IoMT.
The Health Prediction using Cloud Edge 2.0 (HPCE 2.0) algorithm using fuzzy logic to integrate Electronic Health Records (EHRs) and IoMT data.
A blockchain-enhanced architecture with Proof of Authentication 2.0 (PoAh 2.0) for data integrity and Explainable AI (LIME/SHAP) for transparency.

Main Results:

The HPCE 2.0 algorithm accurately predicts individual health severity by handling data uncertainty.
The PoAh 2.0 consensus mechanism ensures data integrity and non-repudiation on a decentralized ledger.
Edge-cloud integration significantly reduces delay for critical real-time alerts, validated by security tests.

Conclusions:

The proposed framework establishes a new standard for interpretable, secure, and responsive AI-driven healthcare.
The system effectively addresses privacy concerns while maintaining high predictive performance, as demonstrated in a cardiac arrest prediction case study.
Integration of XAI transforms AI from a black box into an open collaborator, fostering trust and acceptance.