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Tham YC 32
Showing records 1 to 25 | Display all abstracts from Tham YC104599 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
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Ran AR
Frontiers in medicine 2022; 9: 860574
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
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Wang X
Frontiers in medicine 2022; 9: 860574
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
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Chan PP
Frontiers in medicine 2022; 9: 860574
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Tham YC; Majithia S
British Journal of Ophthalmology 2022; 106: 962-969
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Chan NC
Frontiers in medicine 2022; 9: 860574
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
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
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Yip W
Frontiers in medicine 2022; 9: 860574
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
Frontiers in medicine 2022; 9: 912214
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Young AL; Wong MOM
Frontiers in medicine 2022; 9: 860574
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Xu X
Frontiers in medicine 2022; 9: 912214
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Wong MOM
Frontiers in medicine 2022; 9: 860574
103826 Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Cheung C; Boey PY
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
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Yung HW
Frontiers in medicine 2022; 9: 860574
104599 Smartphone-Acquired Anterior Segment Images for Deep Learning Prediction of Anterior Chamber Depth: A Proof-of-Concept Study
Li J
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
Aung T
British Journal of Ophthalmology 2022; 106: 962-969
104513 Three-Dimensional Multi-Task Deep Learning Model to Detect Glaucomatous Optic Neuropathy and Myopic Features From Optical Coherence Tomography Scans: A Retrospective Multi-Centre Study
Chang RT
Frontiers in medicine 2022; 9: 860574
