| 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 |