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Soh ZD 18
Showing records 1 to 18 | Display all abstracts from Soh ZD104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Qian C
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Thakur S
British Journal of Ophthalmology 2022; 106: 962-969
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Jiang Y
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Yu M
British Journal of Ophthalmology 2022; 106: 962-969
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Soh ZD
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Tham YC
British Journal of Ophthalmology 2022; 106: 962-969
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Sakthi Selvam G
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Majithia S; Soh ZD
British Journal of Ophthalmology 2022; 106: 962-969
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Xiao S
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Fang XL
British Journal of Ophthalmology 2022; 106: 962-969
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Tham YC; Xu X
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Cheung C
British Journal of Ophthalmology 2022; 106: 962-969
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Liu Y
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Boey PY; Aung T
British Journal of Ophthalmology 2022; 106: 962-969
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Li J; Zhong H
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Wong TY
British Journal of Ophthalmology 2022; 106: 962-969
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Cheng CY
Frontiers in medicine 2022; 9: 912214
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Cheng CY
British Journal of Ophthalmology 2022; 106: 962-969
