You are invited to Register (free) and submit an abstract to the Workshop: "AI, Big Data, and Pregnancy Loss", 12 July 2023
Women's reproductive health is probably the least systematically dissected with use of so-called omics technologies and through AI applications, contrary to its importance at individual level.
Although most of the physical and mental health conditions, that women experience, are not considered as directly related to reproduction, the latter has a large impact on the women's health. Many other factors contribute to pregnancy loss susceptibility but there is lack of large datasets to characterise such risk factors, as compared to other common conditions.
The prevalence of women's reproductive issues rapidly increases with older maternal age at conception and overall ageing of populations. As a result, women turn to in-vitro fertilisation, that exacerbates certain reproductive health issues, including pregnancy loss.
This workshop will explore the implementation of AI approaches to combine multiple individual health data characteristics, big 'omic and other data for prediction of women's reproductive health outcomes before and during pregnancy as well as those of the foetus/newborn. We will also discuss how these could be informative for development of health system prevention strategies.
The workshop will feature invited lectures and talks from representatives of clinical and basic research, private companies, and national resources.
Confirmed speakers include:
Prof Ranjit Akolekar, Medway Fetal and Maternal Medicine Centre, Medway NHS Foundation Trust, UK. Pregnancy Loss and related outcomes - clinical perspective from the UK
Dr Natalia Pervjakova, Estonian Biobank, Estonia. The Estonian Biobank's MyGenome Portal: A comprehensive platform for return of results to over 200,000 biobank participants
Dr Ayse Demirkan, University of Surrey, UK. Microbiome and virome analyses for pregnancy loss prevention
The workshop will feature presentations from: Lifebit, Genomics England, Deloitte
The full programme will soon be available on the workshop's website.
To register or submit an abstract visit our Workshop webpage: https://www.ias.surrey.ac.uk/event/ai-big-data-and-pregnancy-loss/
Workshop date/time: Wednesday, 12 July 2023 (9am-5pm)
Location: Innovation for Health Building, Room 02IFH01, Guildford, University of Surrey, Guildford, UK
Email contact: [log in to unmask]<mailto:[log in to unmask]> Follow us on twitter: @StatisticalMultiOmics
Attendance is free but requires registration:
Registration is open / Registration closes 4 July 2023.
In this workshop, we call for contributions from both, practical and theoretical researchers, scholars and academics from the universities, healthcare professionals and private companies on the topic of implementation of artificial intelligent approaches in perinatal health.
Call for Abstracts deadline 4 July 2023
Call for Abstracts notification 5 July 2023
We encourage submissions of short 250-words abstracts on either:
1. AI enabled basic and clinical research for pregnancy complications/loss, miscarriage, recurrent pregnancy loss, stillbirth, cerebral palsy, sudden infant death syndrome (SIDS or cot death)
2. Large-scale datasets that enable big 'omic data, machine learning or AI research for pregnancy loss spectrum and related conditions
3. Novel sensors and technologies using AI to aid prevention of pregnancy complications or loss
4. Open Challenges in pregnancy complications/loss research which may be addressed using big data and AI
If you would like to present your research on the Workshop-related subject, please, submit your abstract (250 words maximum) by selecting the tab "Submit an Abstract" on https://www.ias.surrey.ac.uk/event/ai-big-data-and-pregnancy-loss/ Please, do not enter references in the abstract text.
Workshop organisers:
Prof Inga Prokopenko, Dr Ayºe Demirkan, Dr Adam Mahdi, Dr Yevheniya Sharhorodska
People-Centred AI institute, University of Surrey, Guildford, UK.
Administrative support: [log in to unmask]<mailto:[log in to unmask]>
Prof Inga Prokopenko, PhD
Vice Chancellor's Distinguished Chair
Co-Director of AI institute, Professor of e-One Health,
Head of Section of Statistical Multi-Omics,
Department of Clinical and Experimental Medicine,
School of Biosciences and Medicine, University of Surrey
Email: [log in to unmask]<mailto:[log in to unmask]>
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