Towards a modular decision support system for radiomics : A case study on rectal cancer
- Submitting institution
-
The University of Huddersfield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 66
- Type
- D - Journal article
- DOI
-
10.1016/j.artmed.2018.09.003
- Title of journal
- Artificial Intelligence in Medicine
- Article number
- -
- First page
- 145
- Volume
- 96
- Issue
- -
- ISSN
- 0933-3657
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
11
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This interdisciplinary work, involving experts from The Netherlands, Italy, and UK, led to the development of a decision support system for radiomics that is currently used in daily practice at the Agostino Gemelli Polyclinic ( http://www.gemelli-art.it/research ). The proposed framework extends Vallati and his co-authors’ previous influential work on tools for the automated analysis of prognostic images (https://pubmed.ncbi.nlm.nih.gov/26736376/) that resulted in the widely used Moddicom tool for R (https://rdrr.io/github/kbolab/moddicom/).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
