This work focuses on signs and symptoms recognition in biomedical texts abstracts. First, this specific task is described from a linguistic point of view. Then a methodology combining pattern mining and language processing is proposed. In the absence of an authoritative annotated corpus , our approach has the advantage of being weakly-supervised. Preliminary experimental results are discussed and reveal promising avenues.