Advancing remote consultation through the integration of blockchain and ant colony algorithm

Area of Science:

• Blockchain Technology
• Artificial Intelligence
• Healthcare Management

Background:

• Current medical systems face challenges in resource allocation, fee negotiation, and patient data management.
• Remote consultation services require secure, accurate, and traceable data handling.

Purpose of the Study:

• To propose a decentralized remote intelligent consultation blockchain model.
• To address issues of fair resource allocation, fee negotiation, and patient data privacy in healthcare.

Main Methods:

• Development of a decentralized remote intelligent consultation blockchain model.
• Integration of an improved ant colony algorithm within smart contracts.
• Simulation platform for multi-node remote consultation services.

Main Results:

• The proposed blockchain model facilitates reasonable and fair allocation of medical resources.
• The improved ant colony algorithm effectively matches target populations under smart contracts.
• Demonstrated practicality and automatic execution capabilities of the algorithm in simulations.

Conclusions:

• The decentralized blockchain model offers a viable solution for enhancing remote consultation services.
• Smart contracts with improved ant colony algorithms can optimize healthcare operations and data integrity.