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A Dynamic MooM Dataset Processing Under TelMED Protocol Design for QoS Improvisation of Telemedicine Environment
Syed Thouheed Ahmed1, M Sandhya2, Sharmila Sankar2
1School of Computers, Information and Mathematical Sciences, BSA Crescent Institute of Science and Technology, Chennai, India. Syed.edu.in@gmail.com.
This study introduces a new telemedicine infrastructure for improved remote patient-doctor connectivity. It enhances data processing and transmission quality, boosting the overall Quality of Service (QoS) and Quality of Data (QoD).
Area of Science:
- Medical Informatics
- Computer Science
Background:
- Telemedicine research aims to enhance remote patient-doctor connectivity.
- Current challenges include data optimization and processing over low Quality of Service (QoS) communication channels.
Purpose of the Study:
- To represent and validate a modern telemedicine infrastructure.
- To improve Quality of Service (QoS) and Quality of Data (QoD) for medical data processing.
Main Methods:
- Developed a telemedicine infrastructure with Multiple Objective Optimized Medical dataset (MooM) processing.
- Designed a TelMED protocol for efficient remote medical data transmission and processing.
- Utilized edge computation for Electronic Health Records (EHR) creation and updating.
Main Results:
- The proposed infrastructure demonstrated improved QoS and Quality of Data (QoD) compared to typical communication algorithms.
- Validation through MooM dataset processing and TelMED channel optimization sessions showed significant enhancements.
- Reverse processing of MooM datasets towards the server end for diagnosis confirmed consolidated QoS improvements.
Conclusions:
- The developed telemedicine infrastructure effectively addresses challenges in low QoS environments.
- The MooM processing and TelMED protocol offer a robust solution for remote medical data handling.
- The application-oriented approach enhances EHR management through edge computation, improving overall healthcare delivery.
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