Knowledge-based clinical decision making about radiation in cancer treatement

In the current state of medical practice, radiation-based procedures are essential for diagnosis, prevention, and therapy. To enhance patient care while meeting international regulatory standards, integrating medical informatics and artificial intelligence is crucial. This paper presents a knowledge-based decision support system (DSS) specifically developed for radiation therapy in cancer treatment. The system leverages ontology modeling and rule-based reasoning to assist healthcare professionals in navigating radiation therapy complexities. The DSS comprises an ontology knowledge base, an inference engine, and a communication mechanism. Testing results show that the system achieved a 98% success rate in establishing connectivity and communication between Java and OWL files, a 97% success rate in automating dose compliance reasoning, and a 93% user satisfaction rate. Notably, the system reduced the time required for decision-making by 80% and improved the efficiency of treatment planning by 85%. User feedback also indicated a 95% improvement in data retrieval speed and a 92% enhancement in interface usability. These results demonstrate the system's effectiveness in improving decision-making, ensuring precise radiation dosage control, and streamlining clinical audits within an interoperable framework.