| dc.contributor.advisor | Alam, Md. Golam Rabiul | |
| dc.contributor.author | Joy, Moinul Alam | |
| dc.date.accessioned | 2021-11-21T06:12:35Z | |
| dc.date.available | 2021-11-21T06:12:35Z | |
| dc.date.copyright | 2021 | |
| dc.date.issued | 2021-05 | |
| dc.identifier.other | ID 19166022 | |
| dc.identifier.uri | http://hdl.handle.net/10361/15629 | |
| dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. | en_US |
| dc.description | Cataloged from PDF version of thesis. | |
| dc.description | Includes bibliographical references (pages 51-52). | |
| dc.description.abstract | Nowadays, it has become di cult to get in touch with a doctor for the current pandemic
situation. Patients need to wait several days to get an appointment from the
doctor and visiting the hospitals in recent times is also very risky. So, The main
purpose of this application is to give a patient the basic treatment by given his symptoms
so that he/she can receive medical services in home. This project focuses on
two portions of disease detection. One portion is for common diseases and another
one is for skin diseases. We have used di erent training algorithm for both portions
of disease detection. An online API has been used along with machine learning library
like tensor
ow to produce the results. This mobile application not only shows
the probability of the diseases, but also gives information about the cure or solutions. | en_US |
| dc.description.statementofresponsibility | Mohammad Moinul Alam Joy | |
| dc.format.extent | 52 pages | |
| dc.language.iso | en | en_US |
| dc.publisher | Brac University | en_US |
| dc.rights | Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
| dc.subject | Disease prediction | en_US |
| dc.subject | Support vector machine | en_US |
| dc.subject | Skin disease | en_US |
| dc.subject | MobileNet | en_US |
| dc.subject | Collaborative ltering | en_US |
| dc.subject | Android application | en_US |
| dc.subject.lcsh | Machine learning | |
| dc.subject.lcsh | Application software--Development | |
| dc.subject.lcsh | Mobile computing | |
| dc.title | A decision support system for symptom-based common diseases and image-based skin diseases detection | en_US |
| dc.type | Thesis | en_US |
| dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
| dc.description.degree | B. Computer Science | |
