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Simulation/VR Training in Surgery: a patient-based approach
June 5, 2021 @ 19:30 - 20:30
![](https://www.icsmsu.com/wp-content/uploads/2021/02/7224_image_131072045_659217364746021_4552717089497711243_n-1.jpg)
**This event is cancelled until further notice due to the coronavirus pandemic and altered availabilities of the speaker. We apologise on behalf of Dr Tom Bainton for any inconvenience caused, and look forward to hosting the event in the near future**
This week, in our series of alternative careers in medicine, we have Dr Tom Bainton who’ll be giving a talk on simulation training and minimally invasive surgery!
Tom Bainton is currently the Fellow in Minimally Invasive Gynaecological Surgery at Chelsea and Westminster Hospital, London. This role is mainly focussed on surgery for patients with deep infiltrating endometriosis. He graduated from Oxford University Medial School in 2012 and underwent foundation training in the London Deanery. He commenced speciality training in Obstetrics and Gynaecology in Cambridge in 2014 before returning to London for his current post.
Outside of his clinical role he is a faculty member of the Chelsea Centre for Minimally Invasive Gynaecology (CCMIG), which runs minimal access surgery training courses for delegates both in the UK and internationally through hands-on simulation and online. The Centre is moving to a fully virtual model for some courses to allow continued training through the pandemic, which is run through the online learning platform on the CCMIG website. He has a broad interest in medical education, particularly simulation and innovative training models, and obtained a Postgraduate Certificate in Medical Education from Cambridge University in 2019.
Tom also leads the patient and public involvement arm for CCMIG and the Chelsea and Westminster Hospital Endometriosis Services via social media and YouTube, where they present educational videos for both patients and medical students / trainees. His research interest is in the field of endometriosis by development of a quantitative diagnostic algorithm for this enigmatic condition.
Hope to see you all there!