SMM (SUPPORT MEDICAL MACHINE)
| dc.contributor.author | Askarova A. | |
| dc.contributor.author | Gylymmedden Y. | |
| dc.contributor.author | Temirbekova D. | |
| dc.contributor.author | Sultanova N. | |
| dc.date.accessioned | 2023-12-06T05:15:51Z | |
| dc.date.available | 2023-12-06T05:15:51Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Abstract. Machine learning (ML) provides methods, techniques, and tools that can help solve diagnostic and prognostic problems in various fields of medicine. ML is used to analyze clinical parameters and their combinations for prognosis, such as disease progression, for maintenance therapy of treatment, and for General patient management. In our time, computer systems have already begun to be introduced into the healthcare environment, which makes it possible to facilitate and improve the efficiency of medical professionals and ultimately improve the efficiency and quality of medical care. Below is a demonstration to tell what the main applications of ML were used in the application and show how they can be useful for medical care. The main task was to combine all the useful functions that can help people in the field of medicine. The application will help to determine the authenticity of medicines through text recognition and search through the database of official drug registers, as well as using recommendation systems and algorithms (K-nearest neighbor Algorithm) to help in the selection of medicines, using the camera and phone flash to calculate the heart rate, which will accordingly help people with blood pressure problems. The application will be available on two platforms on 10S, as well as for the Android operating system, as it was implemented through the Flutter framework in Android Studio. For the algorithms, used Google's ML-Kit libraries. Jupyter, numpy, pandas, matplotlib, scipy, and scikit-learn Notepad are also used for data preparation. | |
| dc.identifier.citation | A. Askarova, Y. Gylymmedden, D.Temirbekova, N.Sultanova / А. Асқарова, Е. Ғылыммедден, Д. Темірбекова, Н. Султанова / SMM (SUPPORT MEDICAL MACHINE) / СДУ хабаршысы - 2020 | |
| dc.identifier.issn | 2709-2631 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/907 | |
| dc.language.iso | en | |
| dc.publisher | СДУ хабаршысы - 2020 | |
| dc.subject | machine learning | |
| dc.subject | KNN | |
| dc.subject | medical | |
| dc.subject | recommendation system | |
| dc.subject | image recognition | |
| dc.subject | Flutter | |
| dc.subject | Android | |
| dc.subject | IOS | |
| dc.subject | heart rate | |
| dc.subject | СДУ хабаршысы - 2020 | |
| dc.subject | №2 | |
| dc.title | SMM (SUPPORT MEDICAL MACHINE) | |
| dc.type | Article |