Detection of diseases using machine learning algorithms
| dc.contributor.author | Meraliyev M. | |
| dc.date.accessioned | 2024-12-25T12:21:28Z | |
| dc.date.available | 2024-12-25T12:21:28Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | The recent advancements in computer technologies and storage capabilities have produced an incredible amount of data and information from many sources such as social networks, online databases, and health information systems. Nowadays, many countries around the world are changing the way of implementing health care to the patients and the people by utilising the benefits of advancements in computer technologies and communications through electronic health. This huge amount of data can be tuned into knowledge and more useful form of data by using computing and machine learning tools. It is believed that engineering this amount of data can aid in developing expert systems for decision support that can assist physicians in diagnosing and predicting some debilitating life threatening diseases such as breast cancer. Expert systems for decision support can reduce cost, the waiting time and free human experts (physicians) for more research, as well as reduce the errors and mistakes that can be made by humans due to fatigue and tiredness. However, the process of utilising health data effectively, involves many challenges such as the problem of missing features values, the curse of dimensionality due to a large number of features (attributes), and the course of actions to determine the features, that can lead to more accurate results (more accurate diagnosis). Effective machine learning tools can assist in early detection of diseases such as breast cancer, and the current work in this thesis focuses on investigating novel approaches to diagnose breast cancer based on machine learning tools, and involves development of new techniques to construct and process missing features values, investigate different feature selection methods, and how to employ them into diagnosis process. | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1626 | |
| dc.language.iso | en | |
| dc.subject | machine learning, breast cancer, data mining, algorithm, statistics, development, evolution | |
| dc.title | Detection of diseases using machine learning algorithms | |
| dc.type | Other |