Combining case-based reasoning with Bee Colony Optimization for dose planning in well differentiated thyroid cancer treatment

► We used Case-Based Reasoning to describe a physician’s expertise when treating thyroid cancer. ► We took into account various clinical parameters. ► The weights of these parameters are determined with the Bee Colony Optimization meta-heuristic. ► The proposed CBR–BCO model suggests the I-131 iodine dose in radioactive iodine therapy. ► This approach is tested on real data from the Department of Nuclear Medicine, Serbia. Thyroid cancers are the most common endocrine carcinomas. Case-based reasoning (CBR) is used in this paper to describe a physician’s expertise, intuition and experience when treating patients with well differentiated thyroid cancer. Various clinical parameters (the patient’s diagnosis, the patient’s age, the tumor size, the existence of metastases in the lymph nodes and the existence of distant metastases) influence a physician’s decision-making in dose planning. The weights (importance) of these parameters are determined here with the Bee Colony Optimization (BCO) meta-heuristic. The proposed CBR–BCO model suggests the I-131 iodine dose in radioactive iodine therapy. This approach is tested on real data from patients treated in the Department of Nuclear Medicine, Clinical Center Kragujevac, Serbia. By comparing the results that are obtained through the developed CBR–BCO model with those resulting from the physician’s decision, it has been found that the developed model is highly reflective of reality.