Young Innovator Travel Grants

The Asia Pacific Tele-Ophthalmology Society & the Asia-Pacific Ocular Imaging Society will offer up to 3 travel grants for outstanding presenters and young innovators to attend the 9th APTOS Symposium in Hong Kong. Priority will be given to young innovators who are aged 40 or below, from a developing country, whose presentations (free paper or poster) have been accepted by the Scientific Program Committee of the 9th APTOS Symposium and who have not received the APTOS Young Innovator Travel Grants before. Each successful applicant will receive US$500 in addition to waived registration.

Interested young innovators please click here to apply online. The application deadline is August 15, 2024. Selection results will be announced by August 31, 2024. Don’t miss your chance to become the next rising star.

TIME	TITLE	PRESENTER
17:00-17:07	EyeGPT: Ophthalmic Assistant with Large Language Models	Xiaolan CHEN
17:07-17:14	Prospective Evaluation of Continually Pre-trained Models for Endocrine and Metabolic Diseases Screening via Retinomics: A Retrospective, Prospective, Multicentre Study	Xiayin ZHANG
17:14-17:21	Towards Regulatory Generative AI in Ophthalmology Healthcare: A Security and Privacy Perspective	Yueye WANG
17:21-17:28	Comparative Analysis of Large Language Models for Cataract Care	Harry SU
17:28-17:35	General and Chinese-specific Large Language Models’ Performance for Myopia-related Queries in China	Zehua JIANG
17:35-17:42	FFA-GPT: Automatic Fundus Fluorescein Angiography Image Interpretation with Large Language Models	Xiaolan CHEN
17:42-17:49	The Use of Large Language Models in Ophthalmology: A Scoping Review on Current Use-Cases and the Potential Pitfalls	Alva LIM
17:49-17:56	Comparison of Generative AI-Based Learning versus Text-Only Learning in Ophthalmology among Medical Students – a Non-Randomized Study	Tharini SENTHAMIZH

TIME	TITLE	PRESENTER
11:00-11:08	ChatFFA: An Interactive Chat System for Visual Question Answering on Fundus Fluorescein Angiography Images	Xiaolan CHEN
11:08-11:16	Unveiling Choroidal Vascular Fingerprints: Automatic Segmentation and Multi-dimensional Feature Quantification on Indocyanine Green Angiography via Deep Learning	Ruoyu CHEN
11:16-11:24	Using Optical Coherence Tomography to Evaluate Diabetic Retinal Neurodegeneration in Patients with Referable and Non-referable Diabetic Retinopathy	Adrian LEE
11:24-11:32	Novel Quantitative Analysis of Anterior Chamber Inflammation Based on a Deep Learning Model Using Anterior Segment Optical Coherence Tomography Images for Diagnosis and Precise Assessment of Intraocular Inflammatory Diseases	Ye DAI
11:32-11:40	Quantifying Macular Cone Mosaic Metrics by Adaptive Optics Retinal Camera to Enhance Diagnosis Efficiency in High Myopia Patients	Ke-Yu LIU
11:40-11:48	Hessian-Attentive feature enhanced convolutional neural networkfor OCT image denoising	Jie GAO
11:48-11:56	Assistance of Artificial Intelligence in Diagnosis of Vitreoretinal Lymphoma on Optical Coherence Tomography	Aidi LIN
11:56-12:04	Detection of Stardust Sign in SSOCT Images Using Deep Learning	Mao TANABE

TIME	TITLE	PRESENTER
09:00-09:08	An Integrated Model to Use AI and Teleophthalmology to Screen Glaucoma in a Low Resource Setting	Malinda DE SILVA
09:08-09:16	Supporting Diabetic Macular Edema Triage Screening by a Deep Learning-based OCT Image Analysis: a Prospective Study	Shuyi ZHANG
09:16-09:24	Ultra-Widefield Fundus Imaging for Diabetic Retinopathy Challenge 2024 (UWF4DR)	Bin SHENG
09:24-09:32	Converting Ultra-Widefield Fundus Photography to Ultra-Widefield Fluorescein Angiography via UWAFA-GAN for Diabetic Retinopathy Screening	Zhicong XU
09:32-09:40	Effectiveness, Cost-Effectiveness and Cost-Utility of a Tiered Artificial Intelligence-Enabled Diabetic Eye Care (AID-Eye) Model Starting from Primary Health Care in Rural China	Xiaochen MA
09:40-09:48	An Oculomics Approach: Retinal Vascular Characteristics Modeling for High-Precision Diagnosis of Mild Non-Proliferative Diabetic Retinopathy	Peng XIAO
09:48-09:56	Assessment of Mild Cognitive Impairment via a Retinal-Imaging-Based Deep Learning Model through Majority Voting	Herbert HUI
09:56-10:04	Development and Validation of a Deep Learning Platform for Detecting Multiple Retinal Fundus Diseases	Mingzhi ZHANG
10:04-10:12	Development and Validation of a Deep Learning Algorithm for Detection of Orbital Disease Using Ocular Images from Multi-center Populations	Chaoyu LEI
10:12-10:20	Development and Validation of a Deep Learning Model to Predict the Occurrence and Severity of Retinopathy of Prematurity	Qiaowei WU
10:20-10:28	Mild Cognitive Impairment Screening Based on FusionNet and Ensemble Learning-based Artificial Intelligence System for Alzheimer’s Disease	Andy NG

TIME	TITLE	PRESENTER
17:00-17:08	EyeCLIP: A Visual–Language Foundation Model for Multi-Modal Ophthalmology Image Analysis	Mingguang HE
17:08-17:16	Fine-tuning RETFound for Glaucoma Detection from Color Fundus Photographs	Hin Yin CHAN
17:16-17:24	Augmenting Glaucoma Screening: Real-World Validation of Medios AI Across Multiple Ethnicities and Device-Agnostic Capabilities	Divya RAO
17:24-17:32	Artificial Intelligence-based database for prediction of protein structure and their alterations in ocular diseases	Mingzhi ZHANG
17:32-17:40	Efficiency and Safety of Automated Label Cleaning on Multimodal Retinal Images	Tian LIN
17:40-17:48	Digital Ruler of Strabismus: Smartphone-Based Artificial Intelligence for Strabismus Measurement and Diagnosis	Ruixin WANG
17:48-17:56	Empowering Universal Self-Screening for Malignant Ocular Rare Tumors Using Smartphones	Shaowei BI

TIME	TITLE	PRESENTER
13:00-13:09	Digital Gonioscopy Based on Three-dimensional Anterior-Segment OCT: An International Multicenter Study	Zefeng YANG
13:09-13:18	Universal Bluetooth Integrated Electronic Eyedrop Sleeve : A Novel Compliance Monitoring System for Glaucoma Patients	Neeraj ISRANI
13:18-13:27	Glaucoma Upgrade Intervention Decision-making Enhancer (GUIDE): A Machine Learning-based Telemedicine Solution	Kezheng XU
13:27-13:36	Comparative Study on the Performance of Melbourne RapidFields Web-browser Perimeter to the Humphrey Field Analyzer in Chinese Glaucoma Patients	De-Fu CHEN
13:36-13:45	Predicting Optic Nerve Head Biomechanical Response to Intraocular Pressure Using Patient-Specific Modeling and Machine Learning	Xiaofei WANG
13:45-13:54	Visual Field Patterns of Open-Angle Glaucoma and Potential Associations with Long-term Progression Risks: A Machine-Learning Perspective	Yu-Tzu PING
13:54-14:03	Ciliary Process to Lens Distance in Primary Angle-Closure Glaucoma and its Relationship with Shallow Anterior Chamber: Insights from Ocular Magnetic Resonance Imaging	Yuanbo LIANG
14:03-14:12	Optic Nerve Head Abnormalities in Non-pathologic High Myopia and the Relationship with Visual Field	Jingwen JIANG
14:12-14:21	Optic Nerve Head Perfusion in Lateral Decubitus Position in Patients with Asymmetrical Normal Tension Glaucoma and Obstructive Sleep Apnoea	Tin A TUN
14:21-14:30	Research on the rehabilitative effects of long-term virtual reality visual training on glaucoma-related visual function impairments	Yan LU

APTOS-APOIS 2024

Young Innovator Travel Grants

Free Paper 5: AI 3 (Large Language Models)

Free Paper 4: Ocular Imaging

Free Paper 3: AI 2 (Deep Learning & DR Screening)

Free Paper 2: Artificial Intelligence 1

Free Paper 1: AI & Glaucoma