Computational pathology (CPATH)/Computer Assisted Diagnosis research in breast cancer.
Problem
Diagnosing breast cancer accurately and fairly is a challenge, and using a microscope alone doesn’t always catch unique patterns in cancer cells that could help with treatment.
Project
Dr. Gavin Harris is using AI and machine learning to analyze breast cancer tissue samples. This will allow computers to identify cancer patterns automatically, especially for a specific type of breast cancer (HR+)/(HER2-), while also ensuring that these tools are fair and ethical.
Outcome
The project will make it easier to assess likely breast cancer aggressiveness more easily, accurately and at a lower cost helping doctors choose the best treatment options for each patient based on their unique cancer type.
Future
This work could lead to more personalised breast cancer treatments, allowing patients to get therapies that are better suited to their specific needs, which may improve their health outcomes.
Keep reading
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Can Functional MRI of the Brain help us understand Brain Fog in Women with Breast Cancer?
Up to 70% of women with breast cancer experience cognitive difficulties, but scientists still don't fully understand why this happens. Without a clear understanding of the underlying cause, it is d...
Exploring Better Breast Imaging for Women in Aotearoa New Zealand
Mammograms save lives by finding breast cancer early. But they do not work equally well for everyone.For women with very dense breast tissue, cancer can be harder to see on a standard mammogram. Th...
From Evidence to Action: Expanding the ‘Not a One-Size-Fits-All’ Breast Cancer Screening Model for Aotearoa New Zealand.
Breast cancer screening in Aotearoa New Zealand does not benefit all women equally. Many cancers are still found outside the national screening programme, and Māori and Pacific women can face delay...
