Chari, Aswin;
Adler, Sophie;
Wagstyl, Konrad;
Seunarine, Kiran;
Marcus, Hani;
Baldeweg, Torsten;
Tisdall, Martin;
(2022)
IDEAL approach to the evaluation of machine learning technology in epilepsy surgery: protocol for the MAST trial.
BMJ Surgery, Interventions, & Health Technologies
, 4
(1)
, Article e000109. 10.1136/bmjsit-2021-000109.
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Abstract
Epilepsy and epilepsy surgery lend themselves well to the application of machine learning (ML) and artificial intelligence (AI) technologies. This is evidenced by the plethora of tools developed for applications such as seizure detection and analysis of imaging and electrophysiological data. However, few of these tools have been directly used to guide patient management. In recent years, the Idea, Development, Exploration, Assessment, Long-Term Follow-Up (IDEAL) collaboration has formalised stages for the evaluation of surgical innovation and medical devices, and, in many ways, this pragmatic framework is also applicable to ML/AI technology, balancing innovation and safety. In this protocol paper, we outline the preclinical (IDEAL stage 0) evaluation and the protocol for a prospective (IDEAL stage 1/2a) study to evaluate the utility of an ML lesion detection algorithm designed to detect focal cortical dysplasia from structural MRI, as an adjunct in the planning of stereoelectroencephalography trajectories in children undergoing intracranial evaluation for drug-resistant epilepsy.
| Type: | Article |
|---|---|
| Title: | IDEAL approach to the evaluation of machine learning technology in epilepsy surgery: protocol for the MAST trial |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1136/bmjsit-2021-000109 |
| Publisher version: | http://dx.doi.org/10.1136/bmjsit-2021-000109 |
| Language: | English |
| Additional information: | © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
| UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10143374 |
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