Negation is a complex phenomenon in natural languagethat usually changes the polarity of a sentence, creating anopposition between positive and negative counterparts of the same sentence. Negation detection is a challenging problemin the information extraction field. Negation detection is particularly important in systems aimed extracting knowledge fromproduct review text, where negation changes polarity about products or services. However, due to the complexity of natural language, automatically detecting negated expressionsand their scope in narrative product reviews is not a trivial task.

Radiology reports are one of the most important sources of clinical imaging information. They document critical information about the patient’s health and the radiologist’s interpretation of medical findings. Extracted information from Radiology reports can be used to support clinical research, quality improvement, and evidence-based medicine. However, the information in radiology reports is presented in free text format, which makes the task of structuring the data particularly challenging. Extracting this information manually is not a viable task as it is costly and time-consuming.