| Title: | Enriched Image Based Phenotypes for Health Exploration and Discovery |
| Lead Institution: | Calico Life Sciences LLC |
| Principal investigator: | Dr Madeleine Cule |
Application 44584
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About
Chronic metabolic, cardiovascular, and liver disease are amongst the greatest public health burdens, and there is a paucity of effective treatments. The UK Biobank imaging data provides a new window into the organs involved in these conditions (e.g. heart, liver, pancreas, spleen), as well as systemic changes. The aim of this project is to develop new machine learning methods to better understand the relationship between organ form (as visible on MRI or DEXA) and function. We propose to apply recent advances in artificial intelligence, techniques which have already transformed other fields, to better understand the changes that occur within specific organs, and how these relate to disease. These methods could be used to identify people at risk of disease, to identify genetic or lifestyle factors, or to inform the development of new treatments.5 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 7873 | Abdominal imaging associates body composition with COVID-19 severity | Nicolas Basty (+7) | 2023 | PLOS ONE |
| 7129 | Analysis of MRI-derived spleen iron in the UK Biobank identifies genetic variation linked to iron homeostasis and hemolysis | Elena P. Sorokin (+7) | 2022 | American Journal of Human Genetics |
| 10957 | Artifact-free fat-water separation in Dixon MRI using deep learning | Nicolas Basty (+7) | 2023 | Journal of Big Data |
| 9214 | Kidney shape statistical analysis: associations with disease and anthropometric factors | Marjola Thanaj (+8) | 2023 | BMC Nephrology |
| 8974 | Liver shape analysis using statistical parametric maps at population scale | Marjola Thanaj (+6) | 2024 | BMC Medical Imaging |
Enabling scientific discoveries that improve human health