Download JAR files tagged by patient with all dependencies

This project is a project for the JCoRe Linnaeus Annotator. The dictionary contained herein is used for the recognition of concrete species names in text, e.g. "human", "mouse", "n. furzeri", "c. elegans" etc. It does not contain species proxies, i.e. indirect clues to a species like the word "patient" which most likely refers to a human. For this task there is the project jcore-linnaeus-species-ae-proxies-dict.

This project is a resource for the JULES Linnaeus Annotator. The dictionary contained herein is used for the recognition of concrete species names in text, e.g. "human", "mouse", "n. furzeri", "c. elegans" etc as well as species hints, i.e. indirect clues to a species like the word "patient" which most likely refers to a human. For the task of only finding concrete species names in text, there is the project jcore-linnaeus-species-ae-species-dict.

This project is a resource for the JCoRe Linnaeus Annotator. The dictionaries contained herein are used for the recognition of concrete species names in text, e.g. "human", "mouse", "n. furzeri", "c. elegans" etc as well as species hints, i.e. indirect clues to a species like the word "patient" which most likely refers to a human. Additionally to such rather clear proxies, this project also includes a small dictionary containing maximum-frequency-proxies for genus expressions like "Drosophila" which will be mapped to "D. melanogaster". For the task of only finding concrete species names in text, there is the project jcore-linnaeus-species-ae-species-dict.

Protempa supports the construction of software systems for querying clinical databases, summarizing patient data, detecting clinically significant data patterns in groups of patients or individual patients, and extract, transform and load (ETL). Its special feature, temporal abstraction, supports queries and summarization of data in terms of temporal patterns. Temporal patterns enable robust querying and extraction of clinical history. These patterns include frequencies (at least two, three, etc. of some event or observation); sequences (chemotherapy followed by surgery within 180 days, a hospital encounter followed by another hospital encounter within 30 days); and overlaps (falling platelet counts in the setting of HELLP syndrome).