What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Database
His primary areas of investigation include Retinal, Data mining, Artificial intelligence, Ophthalmology and Retina.
His study on Retinal also encompasses disciplines like
- Retinopathy which connect with Type 1 diabetes,
- Caliber together with Gaussian process.
His Data mining research incorporates themes from Basis, Scalability, Precision and recall, Transitive closure and XML.
His studies deal with areas such as Computer vision and Pattern recognition as well as Artificial intelligence.
His research on Ophthalmology also deals with topics like
- Surgery that intertwine with fields like Fundus,
- Diabetic retinopathy which is related to area like Receiver operating characteristic, Glaucoma, Macular degeneration and Cohort.
His Retina research is multidisciplinary, incorporating perspectives in Blood vessel, Medical imaging, Retinal vascular tortuosity, Blood pressure and Anatomy.
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)
- A prime number labeling scheme for dynamic ordered XML trees (226 citations)
- XClust: clustering XML schemas for effective integration (195 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Data mining, Artificial intelligence, Information retrieval, XML and Retinal.
His Data mining study integrates concerns from other disciplines, such as Scalability, Theoretical computer science, Data structure and Query expansion.
He has researched Artificial intelligence in several fields, including Diabetic retinopathy, Machine learning, Computer vision and Pattern recognition.
He has included themes like Efficient XML Interchange, XML database and XML Schema Editor in his Information retrieval study.
His XML research incorporates themes from Data modeling, Query optimization, Data integration and Database.
His work deals with themes such as Blood pressure, Retina and Caliber, which intersect with Retinal.
He most often published in these fields:
- Data mining (29.97%)
- Artificial intelligence (24.58%)
- Information retrieval (21.89%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (24.58%)
- Deep learning (5.72%)
- Diabetic retinopathy (6.73%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Deep learning, Diabetic retinopathy, Algorithm and Retinal are his primary areas of study.
His research in Artificial intelligence intersects with topics in Machine learning and Pattern recognition.
His Pattern recognition study combines topics in areas such as Grading and Retina.
Mong Li Lee interconnects Ophthalmology, Incidence, Blood pressure and Residual neural network in the investigation of issues within Diabetic retinopathy.
The various areas that Mong Li Lee examines in his Algorithm study include Representation, Epidemiology and Robustness.
His Retinal research incorporates elements of Internal medicine, Kidney disease and Cardiology.
Between 2017 and 2021, his most popular works were:
- Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study. (55 citations)
- Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application (37 citations)
- Deep learning in estimating prevalence and systemic risk factors for diabetic retinopathy: a multi-ethnic study. (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Database
Mong Li Lee focuses on Artificial intelligence, Diabetic retinopathy, Deep learning, Epidemiology and Diabetic retinopathy screening.
His Artificial intelligence study incorporates themes from Global health and Grading.
His Diabetic retinopathy research is multidisciplinary, incorporating elements of Consciousness, Incidence, Field and Mass screening.
Within one scientific family, Mong Li Lee focuses on topics pertaining to Algorithm under Epidemiology, and may sometimes address concerns connected to Receiver operating characteristic, Prospective cohort study, Renal function and Kidney disease.
His Diabetic retinopathy screening research is multidisciplinary, relying on both Tele medicine, Fundus and Medical emergency.
His Stroke risk course of study focuses on Retinal and Feature.
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