AI Workshops

We will be conducting an AI workshop online as a pre-meeting of APTOS-APOIS 2024 on December 13. Details are given as follows:

Date: December 13, 2024 (Friday)
Time: 14:00 – 16:00 (GMT+8)
Venue: Zetta, 1/F, Data Technology Hub, 5 Chun Cheong Street, Tseung Kwan O, Hong Kong
Sponsor: Optain Health

The AI workshop will be conducted in English with hands-on training. Please sign up for the workshop beforehand. To sign up for the workshop, please add ‘AI Workshop’ as an add-on while you register for APTOS-APOIS 2024. The AI workshop is completely free. If you had not chosen the add-on while you registered, you can always go back to edit your registration and add the item to your cart. Click here to sign up now.

TIME	TITLE	INSTRUCTOR
14:00-16:00	Optain Health Workshop Using Generative AI to Train a Clinician User Friendly Agent	Zongyuan GE

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

APTOS-APOIS 2024

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

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