Knowledge representation for lung cancer patients' prognosis
| Autor: | Ana T. Winck, Marcos Cordeiro d'Ornellas, Leonardo Minelli |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
medicine.medical_specialty
Knowledge representation and reasoning Association rule learning business.industry Cancer medicine.disease Data science ComputingMethodologies_PATTERNRECOGNITION Health care medicine Prognostics Medical physics Gradual increase Lung cancer business Reliability (statistics) |
| Zdroj: | Healthcom |
| DOI: | 10.1109/healthcom.2014.7001869 |
| Popis: | The gradual increase of cancer cases worldwide has been posing a need on the use of computing resources to accurately retrieve the information recorded in databases. One can highlight the retrieved information importance from a specialist in order to better evaluate pathological response and predict the cancer patient prognosis. This paper presents a way to represent knowledge of cancer registries with emphasis on prognosis. It makes use data mining techniques to find patterns in data stored for patient's lifetime in similar situations. The work is focused on the generation of association rules to find patterns on these registries in order to measure the patient prognosis and drive healthcare experts conclusions. A validation against international oncology organizations and health publications was also made to ensure data and work reliability. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|