Automatic generation of chemotherapy treatment timelines from electronic health records (EHRs) notes not only streamlines clinical workflows but also promotes better coordination and improvements in cancer treatment and quality of care. This paper describes the submission to the Chemotimelines 2024 shared task that aims to automatically build a chemotherapy treatment timeline for each patient using their complete set of EHR notes, spanning various sources such as primary care provider, oncology, discharge summaries, emergency department, pathology, radiology, and more. We report results from two large language models (LLMs), namely Llama 2 and Mistral 7B, applied to the shared task data using zero-shot prompting.

This paper presents a new web portal with information about the state of the art of natural language processing tasks in Spanish. It provides information about forums, competitions, tasks and datasets in Spanish, that would otherwise be spread in multiple articles and web sites. The portal consists of overview pages where information can be searched for and filtered by several criteria and individual pages with detailed information and hyperlinks to facilitate navigation. Information has been manually curated from publications that describe competitions and NLP tasks from 2013 until 2023 and will be updated as new tasks appear. A total of 185 tasks and 128 datasets from 94 competitions have been introduced.