Research Project
Cluster - To Be Added
Development of Multi-Function Health Technology Applications to Improve Hospital Services in the form of: Portable ECG for Heart Disease Treatment, Machine Learning-based Chat-Bot, and Self Health Monitoring
This Project is Supported by
LPDP - Indonesia Endowment Fund for Education
LPDP Riset Keilmuan 2021/2022
PI: David Agustriawan, S.Kom., M.Sc., Ph.D.
Team Member: To Be Added
External Collaborators: To Be Added
Students Involvement:
To Be Added
This Project is Supported by
LPDP - Indonesia Endowment Fund for Education
- LPDP Riset Keilmuan 2021/2022
- David Agustriawan, S.Kom., M.Sc., Ph.D.
- Development of Multi-Function Health Technology Applications to Improve Hospital Services in the form of: Portable ECG for Heart Disease Treatment, Machine Learning-based Chat-Bot, and Self Health Monitoring
Project Description:
This research begins with the problems that exist in Lira Medika Hospital where it is necessary to increase the efficiency of hospital services and innovate medical devices. The first problem is the ECG examination tool for heart disease, where it is felt that the ECG examination tool in the hospital requires an inefficient process, namely the patient has to come to the hospital and be examined with complex medical devices. Therefore, innovation is needed to create a medical device for ECG examination for heart disease that can be done anywhere with a simple mechanism and accurate results. So the research team from the Indonesian International Institute of Bio Scientia (i3L) looked for ideas and made plans to make a prototype of a portable ECG medical device called CARTOO (Cardiac Tattoo). The second problem is that in the patient service system or “customer care” there are limited service operators and a large number of interactions, so that not all patients who try to interact with the operator can be served. From these problems, i3L made an idea and plan to create a machine learning-based Bot-Chat in a hospital which is expected to accommodate all interactions from patients which is named DIY TECHNOLOGY. Another problem is that there is no independent health monitoring system so that the patient data required for medical record data or examination history is not stored and scheduled properly. This problem causes the need for a manual method by recording in a book where it is felt to be inefficient and the risk of data loss is very high. Based on this problem, the i3L research team came up with an idea and plan to make a prototype of a health service monitoring system in a machine learning-based hospital called DIOVA. From the problems that exist in Lira Medika Hospital and the solution proposed by i3L, namely the development of multi-functional health technology applications, it is hoped that it can improve hospital services and make innovations or new breakthroughs for medical devices.
All Projects with LPDP - Indonesia Endowment Fund for Education
