Emily Boyd
Professor, Docent
Mapping disease-environment connections reported in scientific literature at scale with EasyNER
Author
Summary, in English
Climate change and connected environmental disruptions have a large negative
effect on the health of humans and other species. Improved understanding of
known links in the environment-disease nexus as well as knowledge gaps is
essential to prepare for and mitigate this escalating threat. However, knowledge
fragments are scattered across millions of scientific articles making information
synthesis too complex even for large review consortia. Natural language
processing (NLP) tools could help execute this at scale. Here, we developed an
information synthesis pipeline for mapping links between environmental
processes and diseases which expanded our EasyNER tool. We then applied it to
extract co-mentions from 16.7 million abstracts in PubMed, a large collection of
life science literature, producing a knowledge graph of the environment-disease
nexus.
effect on the health of humans and other species. Improved understanding of
known links in the environment-disease nexus as well as knowledge gaps is
essential to prepare for and mitigate this escalating threat. However, knowledge
fragments are scattered across millions of scientific articles making information
synthesis too complex even for large review consortia. Natural language
processing (NLP) tools could help execute this at scale. Here, we developed an
information synthesis pipeline for mapping links between environmental
processes and diseases which expanded our EasyNER tool. We then applied it to
extract co-mentions from 16.7 million abstracts in PubMed, a large collection of
life science literature, producing a knowledge graph of the environment-disease
nexus.
Department/s
- Cell Death, Lysosomes and Artificial Intelligence
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- LU Profile Area: Proactive Ageing
- LU Profile Area: Nature-based future solutions
- LU Profile Area: Natural and Artificial Cognition
- LTH Profile Area: Engineering Health
- LTH Profile Area: AI and Digitalization
- EpiHealth: Epidemiology for Health
- LUCC: Lund University Cancer Centre
- eSSENCE: The e-Science Collaboration
- LUCSUS (Lund University Centre for Sustainability Studies)
Publishing year
2025
Language
English
Document type
Paper, not in proceeding
Topic
- Public Health, Global Health and Social Medicine
- Earth and Related Environmental Sciences
- Computer and Information Sciences
- Electrical Engineering, Electronic Engineering, Information Engineering
- Basic Medicine
- Agricultural and Veterinary sciences
Keywords
- natural language processing
- Named entity recognition
- environmental health
- environmental toxicology
- Biodiversity
- Climate change
- Artificial intelligence
- Deep learning
- Machine learning
- software
- BioBERT
- SDG 3 - Good Health and Well-being
- SDG 13 - Climate Action
- SDG 15 - Life on Land
- SDG 14 - Life Below Water
- SDG 11 - Sustainable Cities and Communities
Conference name
EurIPS 2025
Conference date
2025-12-02 - 2025-12-07
Conference place
Copenhagen, Denmark
Status
Published
Project
- Biomedical text mining for systems biology
- The Swedish Centre of Excellence on Impacts of Climate Extremes (Climes)
- Artificial intelligence-based text mining for COVID-19 and other areas of medicine
- Environmental toxins as cause of lysosomal damage-induced cell death in animals and humans
- Lund University AI Research
- Revealing drivers of cell death disruption across species and theri links to biodiversity loss and human disease
- Lysosomes in cell death - from molecular mechanisms to new treatment strategies
Research group
- Cell Death, Lysosomes and Artificial Intelligence