Semi-supervised incremental learning with few examples for discovering medical association rules.
Ricardo QuintairosJuan Martinez-RomoJosé Miguel Cantero EscribanoLourdes AraujoPublished in: BMC medical informatics and decision making (2022)
Using a small amount of annotated data (which is easily achievable) leads to results similar to those of a supervised system. The proposal may be an important step for the practical development of techniques for mining association rules and generating new valuable scientific medical knowledge.