Personalizing healthcare services to support decision making in treatment of cancer patients using ontology alignment

The foremost medium of information exchange has been text since ages but with the swift increase in volume of documents it has become a tedious task to organize and retrieve relevant information without the use of text-mining applications. Ontologies are a formal way of representing conceptual knowledge and can be related to text data to assist in this task. There is always a need for accurate interpretation of medical records of cancer patients in deciding intervention plans for proper treatment. However due to the ever changing demand in healthcare services such information sources can be highly variable and may not be suitable for all patients. In this situation the most challenging problem is personalizing healthcare treatment adapted to the patient's medical, social and economic conditions. To manage this problem efficiently the work suggests an ontology alignment model using context aware properties of the system and the patient to facilitate decision making. A patient ontology is mapped to the disease ontology to dynamically transform general treatment options into individual intervention plans most suitable for the patient. The proposed method can be used by medical professionals in recognizing incorrect diagnosis, preventive actions or in identifying co-occurring diseases in the patient.