AI-powered extraction of biomedical relationships from the literature
Channel: SIB - Swiss Institute of Bioinformatics
Date: 24/08/2022

What you will discover: methods to automatically extract biomedical relations from the scientific literature

You are: melanoma/cancer researchers

Speaker: Fabio Rinaldi, Head of NLP research at IDSIA and SIB Group Leader.

Click to access specific sections of the talk: 
- 00:20 The challenge of finding relationships from the literature 
- 01:25 Motivation: leveraging AI to support relationship extraction 
- 02:00 Our approach 
- 03:30 Building the Melanoma Gene Relationship database 
- 06:30 Resulting relationships extracted and statistics 
- 10:25 Validation 
- 12:21 Melanobase browser 
- 13:02 Conclusions

Reference papers and resource:
- Zanoli R et al. An annotated dataset for extracting gene-melanoma relations from scientific literature. J Biomed Semantics. 2022;13(2). https://jbiomedsem.biomedcentral.com/articles/10.1186/s13326-021-00251-3 

- Web demo: https://hltnlp-website.fbk.eu/melanobasedemo/

- OntoGene’s Biomedical Entity Recogniser (OGER): https://oger.nlp.idsia.ch/

Any question about this talk? Contact Fabio at 
fabio.rinaldi[at]idsia.ch
 
More about the speaker:
Dr. Fabio Rinaldi leads the Natural Language Processing (NLP) research group at the Dalle Molle Institute for Artificial Intelligence Research (IDSIA). Previously he was a senior researcher at the Institute of Computational Linguistics of the University of Zurich, where he initiated his biomedical text mining group. An important international collaboration in recent years was with the RegulonDB group at the National University of Mexico, where he was visiting research professor. RegulonDB is one of the major life sciences databases, funded by the US National Institute of Health.   
He acquired and managed numerous projects, with funding from the European Union, the Swiss National Science Foundation, InnoSuisse, large companies (in particular the Pharmaceutical Industry), and private research foundations. He has an academic background in computer science and more than 25 years experience in NLP research, with a specific focus on applications in the biomedical domain, such as automatic analysis of the scientific literature, of clinical reports, and health-related social media discussions. He also authored more than 100 scientific papers in various areas of NLP.  
In addition to his role at IDSIA, he is a group leader at the Swiss Institute of Bioinformatics (SIB), and he is affiliated with the Fondazione Bruno Kessler (Trento, Italy), and the Department of Quantitative Biomedicine (DQBM) of the University of Zurich.

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