Introduction
As part of the Turing's Clinical AI Interest Group, we have formed supra-interest groups in different clinical specialties to bring together clinicians and AI experts in a more focused manner - see webpage for details of all the groups.
The current supra-interest groups are:
- Anaesthetics and Intensive Care
- Medical imaging and computer vision
- AI for Women's Health
- Pathology
- Public Health
- NeuroAI
This online event is the sixth meeting of the AI for Women's Health Group. This group is being lead by Bianca Schor, Kristin Collett Caolo and Annalisa Occhipinti with additional help from the organisers of the Clinical AI Interest Group.
The AI for Women's Health Group is an interdisciplinary community (e.g. clinicians, academics, data scientists, designers, health care professionals, students etc) interested in advancing women's health and how to leverage AI to do so.
The groups goals include:
- Building an interdisciplinary and diverse community of individuals working or interested to work in women's health with (or without) AI.
- Bringing visibility to research on women's health and how AI can help to do so
- Facilitating collaborations and bringing more people to the field
- Offering relevant events & trainings, and sharing resources with the community (mostly online for now).
About the event
In this meeting, we will have talks from:
Speaker: Veronica Blanco Gutierrez, University of Bristol
Title: The future of Fetal Heart Rate monitoring: opportunities to incorporate Social Determinants of Health into decision-support tools.
Bio:
Veronica is a nurse and midwife with over 15 years of experience in research, audit and clinical roles, both in the private and public sector in Spain and the UK. Veronica is undertaking an EPSRC-funded doctoral research at the University of Bristol, which focuses on the incorporation of Social Determinants of Health into AI-driven decision support tools during labour for hypoxia prediction. The potential for this work is to reduce adverse neonatal outcomes, reduce health disparities and provide personalised care. Veronica is passionate about involving women at every step of the research and innovation processes and is leading a project titled “Engaging and involving women from underserved communities in AI research in the context of labour care and digital health”. Veronica is also planning on exploring the implications of algorithmic (un)fairness and the impact of data bias in the context of labour monitoring.
Speaker: Kristin Collett Caolo, University of Cambridge
Title: Data Bias in Femtech: A Social Science Approach.
Bio:
Kristin Collett Caolo is a current PhD student at the University of Cambridge in the Department of Sociology whose research focuses on the development of emerging Femtech and AI in Women’s Health. She holds a BA in Biology from Vassar College in New York and an MSc in Science and Technology Studies from University College London. She previously worked as a clinical researcher in NYC for three years publishing and presenting on surgical patient outcomes related to medical devices. In addition to her PhD, she has conducted research at the University of Cambridge on the efficacy and economics of innovation in the Biotechnology industry.
Register now
Register using this link: https://turing-uk.zoom.us/meeting/register/tJUpdeqqrjMjGdWPA25A29eDHlxhSVM5AVua
