Korot, E;
Gonçalves, MB;
Khan, SM;
Struyven, R;
Wagner, SK;
Keane, PA;
(2021)
Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization.
Current Opinion in Ophthalmology
, 32
(5)
pp. 445-451.
10.1097/ICU.0000000000000785.
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Abstract
PURPOSE OF REVIEW: This article aims to discuss the current state of resources enabling the democratization of artificial intelligence (AI) in ophthalmology. RECENT FINDINGS: Open datasets, efficient labeling techniques, code-free automated machine learning (AutoML) and cloud-based platforms for deployment are resources that enable clinicians with scarce resources to drive their own AI projects. SUMMARY: Clinicians are the use-case experts who are best suited to drive AI projects tackling patient-relevant outcome measures. Taken together, open datasets, efficient labeling techniques, code-free AutoML and cloud platforms break the barriers for clinician-driven AI. As AI becomes increasingly democratized through such tools, clinicians and patients stand to benefit greatly.
| Type: | Article |
|---|---|
| Title: | Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1097/ICU.0000000000000785 |
| Publisher version: | https://doi.org/10.1097/ICU.0000000000000785 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences 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 > Institute of Ophthalmology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10132141 |
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