dc.contributor.author |
De Silva, E. H. D. M |
|
dc.date.accessioned |
2022-02-24T09:33:11Z |
|
dc.date.available |
2022-02-24T09:33:11Z |
|
dc.date.issued |
2021 |
|
dc.identifier.citation |
De Silva, E. H. D. M. (2021) E-Clinic system contact doctor for the patient to prescription with providing symptom prediction system to identify disease. BSc. Dissertation Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2017247 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/733 |
|
dc.description.abstract |
At present, home-based methods have been introduced in many parts of the world. But
they cannot be used for all jobs. Many jobs, as well as the medical field, are facing this
problem. There is no cure. Most medical practice requires symptoms to be diagnosed.
There is no cure for these symptoms.
This project targeting on how patients using doctor consultation in the public health
sector and private health sector depends on the illness can reduce waiting time and
getting better service by understanding the patient situation. Project prototypes for
various diseases that implement key findings, predict, and solve problem component
application. The solution is to create a mobile application to increase the usability and
functionality of the e-Clinic.
The project aims to design a prototype that will help address these issues and assist
medical professionals. It is also intended to provide advice on maintenance. This was
done with the help of self-management practices that could be used to develop it. It was
also possible to find in-depth solutions through a literary survey. The information thus
obtained is being interviewed by medical professionals to make it more accurate and to
provide users with a quiz to learn new solutions. The aim is to improve overall
productivity by providing opportunities to work in hospitals as well as at home." |
en_US |
dc.language.iso |
en |
en_US |
dc.title |
E-Clinic system contact doctor for the patient to prescription with providing symptom prediction system to identify disease |
en_US |
dc.type |
Thesis |
en_US |