Veri madenciliği tekniklerini kullanarak ilaç etkileşiminin düzenlenmesi ve sınıflandırılması
Is this your thesis?
This record came from a bulk archive import. If it’s yours, link it to your profile.
Abstract (EN)
Nowadays, there are thousands of approved drugs that can be used for treating people who have medical problems. Therefore, drug Warnings and Precautions section is intended to identify and describe a discrete set of adverse reactions and other potential safety hazards that are serious or are otherwise clinically significant because they have implications for prescribing decisions or for patient management. In this thesis, proposed tool takes the patient personal information, such as gender, age, pregnancy, the current diseases that the patient suffers from, the current drugs, and the newly diagnosed disease as input and returns the suggested drugs that suit the current patient state. The proposed tool consists of two main phases: data acquisition and data processing. In data acquisition phase, drug information has been collected from different sources including DINTO, DrugBank, RxNorm, and FDA. Moreover, a number of test cases have been designed for evaluating the performance of the proposed tool in different scenarios. The test cases have shown the efficiency with accuracy 96% and effectiveness of the proposed tool
Author
Baraa Taha Yaseen Yaseen
How to Cite
Baraa Taha Yaseen Yaseen (Master Thesis). Veri madenciliği tekniklerini kullanarak ilaç etkileşiminin düzenlenmesi ve sınıflandırılması, 2018, Altınbaş University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Altınbaş University
- The comparison of Samuel P. Huntington's "Clash of Civilizations" and Immanuel Wallerstein's "World Systems Analysis"(2024)
- The moderating role of self-efficacy in the effect of adverse childhood experiences on parenting attitudes(2025)
- Hastane mimarisinde fraktal boyutun bilinçli etkisi: Sıcaklık ve konforun artırılması(2024)
- Design of advanced anomaly detection system based on hybrid machine learning technique with optimized feature selection in wireless sensor network(2025)
- Kanser tedavisi amaçlı nano parçacıkların sentezi ve değerlendirilmesi(2025)
- Altı uzay öğrenme tabanlı tek sınıf sınıflandırma kullanılarak optimize edilmiş bir kötü amaçlı yazılım tespit tekniği(2023)
