Recurrent Neural Networks are a class of artificial neural networks designed for processing sequences of data. Unlike traditional neural networks, RNNs have connections that form directed cycles, enabling them to maintain a 'memory' of previous inputs. This characteristic makes them particularly useful for modeling temporal data, which is common in epidemiological studies.
