AI for Women's Health Meeting - March

Learn more Add to Calendar 03/07/2024 01:00 PM 03/07/2024 02:00 PM Europe/London AI for Women's Health Meeting - March Location of the event
Thursday 07 Mar 2024
Time: 13:00 - 14:00

Event type

Turing Network
Free

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.

The current supra-interest groups are:

  • Anaesthetics and Intensive Care
     
  • Medical imaging and computer vision
     
  • AI for Women's Health

This event is the fourth meeting of the AI for Women's Health Group. This group is being lead by Bianca Schor and Kristin Collett Caolo 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

This is the third meeting of the AI for Women's Health Group.

In this meeting, we will have two talks from:
 

  • Dilara Tank, Masters student visiting University of Cambridge. Title of talk is 'A Systematic Review of AI-Automated Segmentation in Transvaginal Ultrasound Scans'.

 

  • Stephan Romanov, PhD Student at University of Manchester. Title of talk is 'Deep learning for breast cancer risk prediction'.

Stephan Romanov is a PhD student currently entering his third year at the University of Manchester. His background is in mathematics and he was first exposed to medical imaging via an interest in automatic gestation age estimation. He is currently studying Biomedical Imaging with a particular focus on breast cancer risk analysis using deep learning methods.

 

Register now

Organisers

Bianca Schor

PhD student and organiser of the AI for women's health supra-interest group

Dr Annalisa Occhipinti

Associate Professor at Teesside University, Co-organiser of the AI for Women's Health Supra-interest group

Dr Emma Karoune

Senior Researcher - Research Community Building | Tools, Practices and Systems

Vicky Hellon

Senior Research Community Manager, Turing-Roche Partnership | Tools, Practices and Systems