81 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National University of SingaporeSG13 papers
- Agency for Science, Technology and ResearchSG11 papers
- Singapore National Eye CenterSG10 papers
- Bioinformatics InstituteSG6 papers
- Duke-NUS Medical SchoolSG6 papers
- Image and Pervasive Access LaboratorySG6 papers
- Institute of High Performance ComputingSG5 papers
- Nanyang Technological UniversitySG5 papers
- Tokyo Metropolitan UniversityJP3 papers
- Chinese Academy of SciencesCN2 papers
- Duke UniversityUS2 papers
- Harvard UniversityUS2 papers
19 papers
EH-Benchmark Ophthalmic Hallucination Benchmark and Agent-Driven Top-Down Traceable Reasoning Workflow
Xiaoyu Pan, Yang Bai, Ke Zou +5
Medical Large Language Models (MLLMs) play a crucial role in ophthalmic diagnosis, holding significant potential to address vision-threatening diseases. However, their accuracy is…
Artificial Intelligence without Restriction Surpassing Human Intelligence with Probability One: Theoretical Insight into Secrets of the Brain with AI Twins of the Brain
Guang-Bin Huang, M. Brandon Westover, Eng-King Tan +11
Artificial Intelligence (AI) has apparently become one of the most important techniques discovered by humans in history while the human brain is widely recognized as one of the mos…
AI Workflow, External Validation, and Development in Eye Disease Diagnosis
Qingyu Chen, Tiarnan D L Keenan, Elvira Agron +35
Timely disease diagnosis is challenging due to increasing disease burdens and limited clinician availability. AI shows promise in diagnosis accuracy but faces real-world applicatio…
VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence
Jianing Qiu, Jian Wu, Hao Wei +39
We present VisionFM, a foundation model pre-trained with 3.4 million ophthalmic images from 560,457 individuals, covering a broad range of ophthalmic diseases, modalities, imaging…
Single-Input Polarization-Sensitive Optical Coherence Tomography Through a Catheter
Georgia L. Jones, Qiaozhou Xiong, Xinyu Liu +2
Intravascular polarimetry with catheter-based polarization-sensitive optical coherence tomography (PS-OCT) complements the high-resolution structural tomograms of OCT with morpholo…
Federated and distributed learning applications for electronic health records and structured medical data: A scoping review
Siqi Li, Pinyan Liu, Gustavo G. Nascimento +12
Federated learning (FL) has gained popularity in clinical research in recent years to facilitate privacy-preserving collaboration. Structured data, one of the most prevalent forms…
Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Network
Haofeng Liu, Heng Li, Huazhu Fu +4
As an economical and efficient fundus imaging modality, retinal fundus images have been widely adopted in clinical fundus examination. Unfortunately, fundus images often suffer fro…
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study
Yilin Ning, Siqi Li, Marcus Eng Hock Ong +4
Risk scores are widely used for clinical decision making and commonly generated from logistic regression models. Machine-learning-based methods may work well for identifying import…
An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification
Suvidha Tripathi, Satish Kumar Singh, Hwee Kuan Lee
Researchers working on computational analysis of Whole Slide Images (WSIs) in histopathology have primarily resorted to patch-based modelling due to large resolution of each WSI. T…
Inverse Renormalization Group based on Image Super-Resolution using Deep Convolutional Networks
Kenta Shiina, Hiroyuki Mori, Yusuke Tomita +2
The inverse renormalization group is studied based on the image super-resolution using the deep convolutional neural networks. We consider the improved correlation configuration in…
Machine-Learning Study using Improved Correlation Configuration and Application to Quantum Monte Carlo Simulation
Yusuke Tomita, Kenta Shiina, Yutaka Okabe +1
We use the Fortuin-Kasteleyn representation based improved estimator of the correlation configuration as an alternative to the ordinary correlation configuration in the machine-lea…
Resolution enhancement and realistic speckle recovery with generative adversarial modeling of micro-optical coherence tomography
Kaicheng Liang, Xinyu Liu, Si Chen +4
A resolution enhancement technique for optical coherence tomography (OCT), based on Generative Adversarial Networks (GANs), was developed and investigated. GANs have been previousl…
Towards Label-Free 3D Segmentation of Optical Coherence Tomography Images of the Optic Nerve Head Using Deep Learning
Sripad Krishna Devalla, Tan Hung Pham, Satish Kumar Panda +16
Since the introduction of optical coherence tomography (OCT), it has been possible to study the complex 3D morphological changes of the optic nerve head (ONH) tissues that occur al…
Machine-Learning Studies on Spin Models
Kenta Shiina, Hiroyuki Mori, Yutaka Okabe +1
With the recent developments in machine learning, Carrasquilla and Melko have proposed a paradigm that is complementary to the conventional approach for the study of spin models. A…
Multi-Instance Multi-Scale CNN for Medical Image Classification
Shaohua Li, Yong Liu, Xiuchao Sui +4
Deep learning for medical image classification faces three major challenges: 1) the number of annotated medical images for training are usually small; 2) regions of interest (ROIs)…
Angle-Closure Detection in Anterior Segment OCT based on Multi-Level Deep Network
Huazhu Fu, Yanwu Xu, Stephen Lin +5
Irreversible visual impairment is often caused by primary angle-closure glaucoma, which could be detected via Anterior Segment Optical Coherence Tomography (AS-OCT). In this paper,…
Gated-Dilated Networks for Lung Nodule Classification in CT scans
Mundher Al-Shabi, Hwee Kuan Lee, Maxine Tan
Different types of Convolutional Neural Networks (CNNs) have been applied to detect cancerous lung nodules from computed tomography (CT) scans. However, the size of a nodule is ver…
Embedded deep learning in ophthalmology: Making ophthalmic imaging smarter
Petteri Teikari, Raymond P. Najjar, Leopold Schmetterer +1
Deep learning has recently gained high interest in ophthalmology, due to its ability to detect clinically significant features for diagnosis and prognosis. Despite these significan…
Multi-Context Deep Network for Angle-Closure Glaucoma Screening in Anterior Segment OCT
Huazhu Fu, Yanwu Xu, Stephen Lin +5
A major cause of irreversible visual impairment is angle-closure glaucoma, which can be screened through imagery from Anterior Segment Optical Coherence Tomography (AS-OCT). Previo…