What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Ophthalmology
- Retina
His primary scientific interests are in Ophthalmology, Retinal, Optical coherence tomography, Glaucoma and Nerve fiber layer.
His work carried out in the field of Ophthalmology brings together such families of science as Diabetic retinopathy, Optometry, Intraclass correlation and Linear regression.
His Retinal study combines topics in areas such as Eye disease, Surgery, Blood pressure, Pathology and Retina.
His Optical coherence tomography research includes themes of Anterior chamber angle, Repeatability, Tomography and Coefficient of variation.
His Glaucoma study incorporates themes from Optical imaging and Receiver operating characteristic.
His Receiver operating characteristic research is multidisciplinary, incorporating perspectives in Diabetic retinopathy screening and Cohort.
His most cited work include:
- Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes. (619 citations)
- Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes. (619 citations)
- Retinal nerve fiber layer imaging with spectral-domain optical coherence tomography: a variability and diagnostic performance study. (375 citations)
What are the main themes of his work throughout his whole career to date?
Ophthalmology, Retinal, Optical coherence tomography, Glaucoma and Diabetic retinopathy are his primary areas of study.
His research investigates the link between Ophthalmology and topics such as Optometry that cross with problems in Refractive error.
His Retinal research integrates issues from Diabetes mellitus, Retina, Internal medicine and Cardiology.
Coefficient of variation is closely connected to Intraclass correlation in his research, which is encompassed under the umbrella topic of Optical coherence tomography.
While the research belongs to areas of Glaucoma, he spends his time largely on the problem of Artificial intelligence, intersecting his research to questions surrounding Pattern recognition.
His research integrates issues of Fundus and Incidence in his study of Diabetic retinopathy.
He most often published in these fields:
- Ophthalmology (57.85%)
- Retinal (55.27%)
- Optical coherence tomography (23.89%)
What were the highlights of his more recent work (between 2018-2021)?
- Ophthalmology (57.85%)
- Retinal (55.27%)
- Glaucoma (23.42%)
In recent papers he was focusing on the following fields of study:
Carol Y. Cheung mainly focuses on Ophthalmology, Retinal, Glaucoma, Optical coherence tomography and Diabetic retinopathy.
His Ophthalmology study integrates concerns from other disciplines, such as Diabetes mellitus and Epidemiology.
Carol Y. Cheung has included themes like Retina, Internal medicine, Disease and Cardiology in his Retinal study.
Carol Y. Cheung works mostly in the field of Glaucoma, limiting it down to topics relating to Visual field and, in certain cases, Glaucoma screening and Optic disc, as a part of the same area of interest.
His work deals with themes such as Optometry, Deep learning, Artificial intelligence and Refractive error, which intersect with Optical coherence tomography.
Carol Y. Cheung focuses mostly in the field of Diabetic retinopathy, narrowing it down to matters related to Cohort and, in some cases, Confounding.
Between 2018 and 2021, his most popular works were:
- Spectral-Domain OCT Measurements in Alzheimer's Disease: A Systematic Review and Meta-analysis. (85 citations)
- Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs. (56 citations)
- OCT Angiography Metrics Predict Progression of Diabetic Retinopathy and Development of Diabetic Macular Edema: A Prospective Study. (48 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Ophthalmology
- Retina
His main research concerns Ophthalmology, Retinal, Glaucoma, Epidemiology and Artificial intelligence.
His Ophthalmology research is multidisciplinary, relying on both Diabetes mellitus, Diabetic retinopathy and Choroid.
His Diabetic retinopathy research incorporates elements of Consciousness and Referral.
Carol Y. Cheung has researched Retinal in several fields, including Body mass index and Disease.
His Glaucoma research incorporates themes from Retinal imaging, Macular degeneration, Margin and Dementia diagnosis, Dementia.
The concepts of his Artificial intelligence study are interwoven with issues in Fundus photography, Fundus and Pattern recognition.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
