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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
outreach
The Blackett Lab Family
Published:
A network of UK based Black Physicists.
IOP Looking Glass Podcast
Published:
Speaking on Series 1 Episode 6: ‘A Blueprint for the Future.’
Project Partners Education
Published:
An educational charity that promotes project-based learning.
Public Engagement
Published:
A list of public-facing events and featured-in articles.
publications
Development and Evaluation of Intraoperative Ultrasound Segmentation with Negative Image Frames and Multiple Observer Labels
Published in Simplifying Medical Ultrasound. ASMUS 2021. Lecture Notes in Computer Science, 2021
This work shares practical experience dealing with variability during image segmentation for prostate cancer patients.
Recommended citation: Chalcroft L.F. et al. (2021) Development and Evaluation of Intraoperative Ultrasound Segmentation with Negative Image Frames and Multiple Observer Labels. In: Noble J.A., Aylward S., Grimwood A., Min Z., Lee SL., Hu Y. (eds) Simplifying Medical Ultrasound. ASMUS 2021. Lecture Notes in Computer Science, vol 12967. Springer, Cham. https://doi.org/10.1007/978-3-030-87583-1_3
Interpretable machine learning for dementia: a systematic review
Published in Alzheimer's & Dementia, 2023
A systematic review of interpretable machine learning applications to dementia.
Recommended citation: Martin, SA, Townend, FJ, Barkhof, F, Cole, JH. Interpretable machine learning for dementia: A systematic review. Alzheimer's Dement. 2023; 1-15. https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.12948
talks
Evaluating Explanation Methods in Deep Learning for Neuroimaging using Stroke Classification as a Ground Truth
Published:
I was selected to present a flash talk at the 1st UCL Institute of Healthcare Engineering Early Career Symposium. This involved giving a brief summary of my research project to an audience with a range of backgrounds.
Explanation Methods in Deep Learning for Stroke Classification
Published:
This talk was part of the 15th Annual London Hopper Colloquium which is an event aimed at Women in Computer Science organised by UCL and the BCS Academy of Computing. My abstract was chosen to be part of a list of finalists, each giving a short presentation on their research to a general audience.
Evaluating Explanation Methods in Deep Learning for Neuroimaging using Stroke Classification as a Ground Truth
Published:
I was invited to deliver an oral presentation as part of a symposium on Explainable Artificial Intelligence in Neuroimaging Symposium at the Organisation for Human Brain Mapping Conference 2024 in Seoul, Korea. My talk recording is available here.
teaching
Postgraduate Teaching Assistant
Masters course, University College London, Department of Computer Science, 2021
I was a teaching assistant on the module Introduction to Deep Learning. This included a guest lecture on Model Interpretation summarising current state-of-the-art approaches to interpretability and explainability in machine learning.