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1.
Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment.
Br J Ophthalmol
; 108(4): 536-545, 2024 Mar 20.
Artículo
en Inglés
| MEDLINE | ID: mdl-37094835
2.
Pegcetacoplan Treatment and Consensus Features of Geographic Atrophy Over 24 Months.
JAMA Ophthalmol
; 2024 May 09.
Artículo
en Inglés
| MEDLINE | ID: mdl-38722644
3.
Evaluating the Effects of C3 Inhibition on Geographic Atrophy Progression from Deep-Learning OCT Quantification: A Split-Person Study.
Ophthalmol Ther
; 12(6): 3143-3158, 2023 Dec.
Artículo
en Inglés
| MEDLINE | ID: mdl-37715860
4.
Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study.
Lancet Digit Health
; 5(6): e340-e349, 2023 06.
Artículo
en Inglés
| MEDLINE | ID: mdl-37088692
5.
Phenotyping of ABCA4 Retinopathy by Machine Learning Analysis of Full-Field Electroretinography.
Transl Vis Sci Technol
; 11(9): 34, 2022 09 01.
Artículo
en Inglés
| MEDLINE | ID: mdl-36178783
6.
Enablers and Barriers to Deployment of Smartphone-Based Home Vision Monitoring in Clinical Practice Settings.
JAMA Ophthalmol
; 140(2): 153-160, 2022 Feb 01.
Artículo
en Inglés
| MEDLINE | ID: mdl-34913967
7.
Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study.
Lancet Digit Health
; 3(10): e665-e675, 2021 10.
Artículo
en Inglés
| MEDLINE | ID: mdl-34509423
8.
The deposition and imaging of silica sub-micron particles in dentine.
J Dent
; 43(10): 1242-8, 2015 Oct.
Artículo
en Inglés
| MEDLINE | ID: mdl-26260975
9.
Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography.
J Biomed Opt
; 20(9): 096001, 2015 Sep.
Artículo
en Inglés
| MEDLINE | ID: mdl-26325264
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