MICA: InterdisciPlInary Collaboration for EfficienT and Effective Use of Clinical Images in Big Data Health Care RESearch: PICTURES (Programme Grant) (Joint with Universities of Edinburgh and Abertay)

Doney, Alexander (Investigator)
Jefferson, Emily (Investigator)
Palmer, Colin (Investigator)
Steele, Douglas (Investigator)
Trucco, Manuel (Investigator)
Wang, Huan (Investigator)

Status	Finished
Effective start/end date	1/08/19 → 28/02/25

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

SDG 3 Good Health and Well-being

Health Informatics Centre
Health and Clinical Services
Facility/equipment: Facility

1 Invited talk

Designing machine learning experiments using SLURM within a Cloud Trusted Research Environment
Cole, C. (Contributor), Reel, P. (Speaker), Jackson, A. (Contributor), Krueger, S. (Contributor), Doney, A. (Contributor) & Steele, D. (Contributor)
5 Sept 2023
Activity: Talk or presentation types › Invited talk

12 Article
3 Review article
3 Preprint
1 Chapter
More
- 1 Poster
- 1 Software

Predicting future dementia from routine clinical MRI and linked healthcare data
Reel, P. S. (Lead / Corresponding author), Al-Wasity, S., Edwards, C., Reel, S., Mansouri-Benssassi, E., Suveges, S., Mookiah, M. R. K., Krueger, S., Trucco, M., Jefferson, E., Doney, A. & Steele, D., 14 Jul 2026, In: Alzheimer's Research and Therapy. 18, 11 p., 164.
Research output: Contribution to journal › Article › peer-review

Open Access
File
3 Downloads (Pure)
An end-to-end workflow for routine clinical MRI brain scans and linked prospective electronic medical records to predict future dementia using a Support Vector Machine (SVM) based Machine Learning Approach: A Feasibility Study
Reel, P. S., Al-Wasity, S., Edwards, C., Reel, S., Mansouri-Benssassi, E., Suveges, S., Krueger, S., Jefferson, E., Doney, A. & Steele, D., 25 Feb 2025.
Research output: Contribution to conference › Poster › peer-review

Open Access
File

75 Downloads (Pure)
Dementia Cohort Identification and SVM Classifier Pipeline for article ‘Machine learning-based prediction of future dementia using routine clinical MRI brain scans and healthcare data’
Reel, P. S. (Creator), Al-Wasity, S. (Creator), Edwards, C. (Creator), Reel, S. (Creator), Mansouri-Benssassi, E. (Creator), Suveges, S. (Creator), Mookiah, M. R. K. (Creator), Krueger, S. (Creator), Trucco, M. (Creator), Jefferson, E. (Creator), Doney, A. (Creator) & Steele, D. (Creator), 29 Oct 2025
Research output: Non-textual form › Software

Open Access

MICA: InterdisciPlInary Collaboration for EfficienT and Effective Use of Clinical Images in Big Data Health Care RESearch: PICTURES (Programme Grant) (Joint with Universities of Edinburgh and Abertay)

Project Details

UN Sustainable Development Goals

Fingerprint

Health Informatics Centre

Designing machine learning experiments using SLURM within a Cloud Trusted Research Environment

Predicting future dementia from routine clinical MRI and linked healthcare data

An end-to-end workflow for routine clinical MRI brain scans and linked prospective electronic medical records to predict future dementia using a Support Vector Machine (SVM) based Machine Learning Approach: A Feasibility Study

Dementia Cohort Identification and SVM Classifier Pipeline for article ‘Machine learning-based prediction of future dementia using routine clinical MRI brain scans and healthcare data’

MICA: InterdisciPlInary Collaboration for EfficienT and Effective Use of Clinical Images in Big Data Health Care RESearch: PICTURES (Programme Grant) (Joint with Universities of Edinburgh and Abertay)

Project Details

UN Sustainable Development Goals

Fingerprint

Equipment

Health Informatics Centre

Activities

Designing machine learning experiments using SLURM within a Cloud Trusted Research Environment

Research output

Predicting future dementia from routine clinical MRI and linked healthcare data

An end-to-end workflow for routine clinical MRI brain scans and linked prospective electronic medical records to predict future dementia using a Support Vector Machine (SVM) based Machine Learning Approach: A Feasibility Study

Dementia Cohort Identification and SVM Classifier Pipeline for article ‘Machine learning-based prediction of future dementia using routine clinical MRI brain scans and healthcare data’