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Edición Especial Special Issue Noviembre 2019
DOI: http://dx.doi.org/10.17993/3ctecno.2019.specialissue3.121-131
Table 1. Methodology Stages.
Stages Description
Stage 1
Problems, solutions and methodology identiî‚¿cation phase. The target
scopes are NTDs, Casemix, IEHSM, Therapeutic approaches, Big Data
Analytics, Artiî‚¿cial Intelligent, Machine Learning, Cloud Computing and
Information Centric Networking. Hence this phase focuses on identifying
research problems and research gap for NTDs and Casemix system
environment. Also, to î‚¿nd the possible solutions and methodology offered by
Big Data Analytics, Artiî‚¿cial Intelligent, Machine Learning, Cloud Computing
and Information Centric Networking that satisî‚¿es the improvement of public
health especially NDTs. Additionally, other critical system information and
system parameters that affect the functionality of the IEHSM system will also
be identiî‚¿ed.
Stage 2
Framework design and implementation phase. This phase focuses on how to
initialize solution and satisfy the information requirement to develop IEHSM
environment. In order to accomplish this goal, by using stage 1 results the
baseline model for the proposed IEHSM will be logically drawn. Based on
the baseline design, the pseudo code/owchart, communication process,
mathematical models and algorithm will then be developed.
Stage 3
Evaluation and results analysis phase. The proposed IEHSM will be
analyzed through user acceptance test. The performance will be evaluated
and benchmark with existing system.
This research will produce preliminary analysis for IEHSM in order to adapt new
ICD-11 and therapeutic prevention approaches. As per above research background,
the following research questions and objectives mapping are formulated and
presented in Table 2.
Table 2. Research Questions and Objectives.
Research Questions Research Objectives
How to intelligently adapt prevention
approaches in IEHSM?
To intelligently adapt prevention
approaches in IEHSM
How to employ Big Data Analytics,
Artiî‚¿cial Intelligent, Machine Learning,
Cloud Computing and Information Centric
Networking for an effective IEHSM
environment?
To employ Big Data Analytics, Artiî‚¿cial
Intelligent, Machine Learning and Cloud
Computing for an effective IEHSM
environment.
How to efî‚¿ciently provide approachable,
interesting, deliverable and public friendly
IEHSM system?
To efî‚¿ciently provide approachable,
interesting, deliverable and public
friendly IEHSM system.