This work presents a brief review of some selected knowledge-based approaches to electrocardiographic (ECG) pattern interpretation for diagnosing various malfunctions of the human heart. The knowledge-based approaches discussed here include modeling an ECG pattern through an AND/OR graph, a rule-based approach and a procedural semantic network (PSN) based approach for ECG interpretation. However, certain syntactic approaches to ECG interpretation are also covered, considering their precursory roles to knowledge-based ECG interpretation. A fuzzy-logic-based approach is included in the discussion to show how imprecision can be dealt with in modeling cardiological knowledge. A domain-dependent control algorithm is discussed to show how the production level parallelism can be exploited to reduce the length of the match}resolve}act cycle of a rule based ECG interpretation system. The review also contains a brief description of some recent applications of connectionist approaches to ECG interpretation. This discussion "nally ends with a comparative assessment of performances of all the above-mentioned knowledge-based approaches to ECG interpretation and some hints about the future directions of work in this "eld.