Competitive analysis about online problem of kidney transplantation acceptance decision-making

The decision-making of the kidney transplantation acceptance is studied and a competitive analysis method is proposed, when only the current and previous treatment information is held by patients. Patients are recognized as curable and incurable, and two online algorithms for these two kinds of patients are proposed. The first algorithm concerns with either continuing the treatment or accepting kidney transplantation by considering and comparing the total treatment spending and the transplantation cost, while the second one concerns with either waiting for more suitable kidney resource or accepting transplantation immediately by comparing the treatment spending between two transplantation chances and improvement quantum of immunity cost after transplantation operation. Then the set of online algorithms for curable patients are presented. These online algorithms are evaluated by introducing a risk reward model into the competitive analysis. Results show that the ratio of the spendings caused by both the online algorithms and the offline algorithms are less than 2. Patients can choose online algorithms by their own treatment expectations and risk tolerance to obtain corresponding risk compensation with a minimum treatment spending.