Text-to-image artificial intelligence to aid clinicians in perceiving unique neuro-ophthalmic visual phenomena
Ir J Med Sci
.
2023 Dec;192(6):3139-3142.
doi: 10.1007/s11845-023-03315-8.
Epub 2023 Feb 14.
Authors
Ethan Waisberg
1
,
Joshua Ong
2
,
Mouayad Masalkhi
3
,
Nasif Zaman
4
,
Sharif Amit Kamran
4
,
Prithul Sarker
4
,
Andrew G Lee
5
6
7
8
9
10
11
12
,
Alireza Tavakkoli
4
Affiliations
1
University College Dublin School of Medicine, Belfield, Dublin 4, Ireland.
[email protected]
.
2
Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.
3
University College Dublin School of Medicine, Belfield, Dublin 4, Ireland.
4
Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA.
5
Center for Space Medicine, Baylor College of Medicine, Houston, TX, USA.
6
Department of Ophthalmology, Blanton Eye Institute, Houston Methodist Hospital, Houston, TX, USA.
7
The Houston Methodist Research Institute, Houston Methodist Hospital, Houston, TX, USA.
8
Departments of Ophthalmology, Neurology, and Neurosurgery, Weill Cornell Medicine, New York, NY, USA.
9
Department of Ophthalmology, University of Texas Medical Branch, Galveston, TX, USA.
10
University of Texas MD Anderson Cancer Center, Houston, TX, USA.
11
Texas A&M College of Medicine, Bryan, TX, USA.
12
Department of Ophthalmology, The University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
PMID:
36787030
DOI:
10.1007/s11845-023-03315-8
No abstract available
Keywords:
Extended reality; Patient perception of disease; Space medicine.
Publication types
Letter
MeSH terms
Artificial Intelligence*
Face
Humans
Neurology*
Vision Disorders
Grants and funding
80NSSC20K183/National Aeronautics and Space Administration