Text Extraction, Analytics and MiningOur research TEAM investigates methodologies for the extraction of both explicit and implicit knowledge from large collections of textual documents, in particular in the domains of life sciences and health-care.

What we do?

Our research combines methods from computational lingustics (e.g. shallow parsing, local grammar modelling), knowledge representation (ontologies) and intensive data mining (feature selection, classification and clustering). Our main focus is in the domains of healthcare and medicine (patient/hospital records) and biology (biomedical literature), but we also investigate other domains/genres (e.g. blogs).

Health-Related Information Synthesis

Synthesis of information from unstructured electronic health-care records, patient narratives and literature to support clinical decision support; sentiment mining of health-related social media.

Large-Scale Extraction And Contextualization Of Biomolecular Events

Extraction of host-pathogen interactions; conflicting statements in scientific texts.

Mining Of Scientific Methodologies From Literature

Capturing best and common practice for in-silico experiments.

Mining Semi-Structured Reports

Data quality in question-answer reports.

Who we are?

We are part of the Text Mining/NLP research group within the School of Computer Science at the University of Manchester, and are based in the IT building (number 40 on the campus map; room IT301). We are affiliated to the Manchester Institute of Biotechnology and closely collaborate with Bio-Health Informatics Group, NIBHI and Biomedical DSS team.
The gnTEAM was established in 2004 and is led by Dr Goran Nenadic.

Recent projects

Our research projects are focused on developing techniques for large-scale extraction and management of un- and semi-structured textual resources.

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We currently run a number of projects to extract various structured data from unstructured clinical narratives and electronic health…

This project is carried out in collaboration with the Clinical Knowledge Management Research Team at Manchester. The team, originate…

The main aim of the Linked2Safety project is to explore the Semantic Web and Linked Data to facilitate semantic interlinking of elec…

Recent publications

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Nikola Milosevic, Cassie Gregson, Robert Hernandez, Goran Nenadic
Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016): International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016). Rome, 2016

Wu, Chengkun; Schwartz, Jean-Marc; Brabant, Georg; Peng, Shao-Liang; Nenadic, Goran
BMC systems biology, 2015

Stoney, Ruth A; Ames, Ryan M; Nenadic, Goran; Robertson, David L; Schwartz, Jean-Marc
BMC systems biology, 2015