Big data for knowledge extraction - COVID19 examples (ScanBaltForum2020)

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A short presentation from the Scan Balt Digital Forum 2020 about the use of big data and artificial intelligence in medicine, with examples related to COVID19.

Health & Medicine

Using Big data to
extract knowledge
examples from COVID-19
Sonja Aits
Cell Death, Lysosomes and Artificial Intelligence Group,
Lund University &
Lund Institute of Advanced Neutron and X-Ray Science
ScanBalt Digital Forum 2020, Sept 4

Medical knowledge is abundant but scattered
Patient journals Bioinformatics databasesScientific literature
Virus Host Drugs

Data
Viral and host sequences
Expression profiles
Protein structures
Drug screening
Biochemical assays
Literature
Imaging data
Health data
Epidemiology data
Mobility data
Resources
Databases
Infrastructures
Software
Artificial intelligence models
3D printing
Consultations
Networks
Discussion groups
Training
Links to resource collections

Artificial intelligence can find and connect
COVID-19 knowledge pieces
Named entity
recognition
Named entity
linking
Relationship
extraction
www.aitslab.org

AI systems can detect disease outbreaks
News articles
Social media
Government/NGO reports
Public mailing lists
Health care records
Self-reporting apps
Web searches
Emergency calls
…
Pandemic
surveillance

How can we
facilitate AI-
based analysis
of big data in
medicine?
• Sharing of data, code and AI models
• Standardization (metadata/data formats,
identifiers, language)
• Centralized metadata repositories
• Accessible long-term data storage
• Detailed documentation (experimental
protocols, data processing, licence)
• Systematic quality control
• Data anonymization
• Open discourse about ethical issues

AI, Cell Death and Lysosomes Group
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Salma Kazemi Rashed
Annie Tallund
Sofi Flink
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Jennie Karlsson
Jesper Laurell
William Lindholm
Viktor Bard
Rasmus Lindqvist
Sonja Kenari
Petter Berntsson
Alexander Skafte
Mariam Miari
Pierre Nugues, LTH, Lund University
Marcus Klang, LTH, Lund University
Johan Frid, Humanities Lab, Lund University
Johanna Berg, Skåne University Hospital
Martin Gerdin Wärnberg, Karolinska Institute
Nick Jackson, CEPI
Maria Björklund, Cochrane Sweden
Swedish National Veterinary Institute

https://youtu.be/C95pl11zdAs Many countries around the world are starting to organise national health data research networks, investing hundreds of millions of dollars, euros, yuan, pounds, etc. in such initiatives. Some of these are organized by the government, such as the NIH All of Us Program in the U.S. and Genomics England, others are started by businesses such as PatientsLikeMe or by patient organizations such as DuchenneConnect. And then there are research-driven infrastructures such as ELIXIR and BBMRI and multi-stakeholder initiatives such as PCORI and HealthRI. During this webinar, we are going to discuss the current technical practice of establishing health data research infrastructures, our experience in building them or advising on that, and the key elements of success that one should not overlook in order to build a healthy, long-lasting health data research network.

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Big data for knowledge extraction - COVID19 examples (ScanBaltForum2020)

1. Using Big data to extract knowledge examples from COVID-19 Sonja Aits Cell Death, Lysosomes and Artificial Intelligence Group, Lund University & Lund Institute of Advanced Neutron and X-Ray Science ScanBalt Digital Forum 2020, Sept 4

2. Medical knowledge is abundant but scattered Patient journals Bioinformatics databasesScientific literature Virus Host Drugs

3. Medical knowledge is abundant but scattered Patient journals Bioinformatics databasesScientific literature Virus Host Drugs

4. Data Viral and host sequences Expression profiles Protein structures Drug screening Biochemical assays Literature Imaging data Health data Epidemiology data Mobility data Resources Databases Infrastructures Software Artificial intelligence models 3D printing Consultations Networks Discussion groups Training Links to resource collections

5. Artificial intelligence can find and connect COVID-19 knowledge pieces Named entity recognition Named entity linking Relationship extraction www.aitslab.org

6. AI systems can detect disease outbreaks News articles Social media Government/NGO reports Public mailing lists Health care records Self-reporting apps Web searches Emergency calls … Pandemic surveillance

7. How can we facilitate AI- based analysis of big data in medicine? • Sharing of data, code and AI models • Standardization (metadata/data formats, identifiers, language) • Centralized metadata repositories • Accessible long-term data storage • Detailed documentation (experimental protocols, data processing, licence) • Systematic quality control • Data anonymization • Open discourse about ethical issues

8. AI, Cell Death and Lysosomes Group Lund University Salma Kazemi Rashed Annie Tallund Sofi Flink Antton Lamarca Jennie Karlsson Jesper Laurell William Lindholm Viktor Bard Rasmus Lindqvist Sonja Kenari Petter Berntsson Alexander Skafte Mariam Miari Pierre Nugues, LTH, Lund University Marcus Klang, LTH, Lund University Johan Frid, Humanities Lab, Lund University Johanna Berg, Skåne University Hospital Martin Gerdin Wärnberg, Karolinska Institute Nick Jackson, CEPI Maria Björklund, Cochrane Sweden Swedish National Veterinary Institute

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