Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions
Abstract
:1. Introduction
1.1. General Aspects
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- Information is stored and processed throughout the network—it is global, not local.
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- A key feature is the plasticity—the ability to adapt, to learn
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- Knowledge is stored in inter-neural connections (synaptic weights).
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- The ability to generalize—artificial neural networks can find the correct answers for slightly different inputs than those for which they were initially trained.
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- The ability to synthesize—can give correct answers for input affected by noise/inaccurate/partial.
1.2. ANN Ophthalmology Reviews
2. Methodology
2.1. Database Searches
2.2. Eligibility Criteria
2.3. Study Selection
3. Results
3.1. Brief Presentation of the Use of Artificial Neural Networks in Medicine
Domain | Input Data | Output Information | Neural Network Use | References |
---|---|---|---|---|
Surgery | Pathological images | distinction of prostate nodules as benign or malignant | RNA ProstAsure Index | [18,19] |
Oncology | Pathological images | diagnosis of cervical lesions, gastric (13), thyroid (14) lesions in determining the oral epithelial cells (15), and identifying the malignant urothelial cells (16), as well as in classifying the cells in pleural and peritoneal exudate (17) | System PAPNET | [22,23,24,25,26,27] |
CT, MRI, radioisotopic scans | detection of brain tumors | RNA | [29,30,31,44] | |
Cardiology, neurology | EKG, EEG, EMG | diagnose myocardial infarction or fibrillation ventricular arrhythmias, EEG analysis in diagnosing epilepsy (25), and sleep disorder analysis of EMG (27) or Doppler ultrasound (28). | RNA | [32,33,34,35,36,37] |
Cancer diagnosis, Pneumology diagnosis, dentistry | Pathology images, X-ray images | classification of images classification of breast cancer detection of pneumonia classification of chest pathologies classification of dental caries classification of X-rays reading chest X-rays identification of the spine and pelvis in frontal X-rays | convolutional neural networks (CNN) | [10,28,38,39,40,41,42,43] |
Medical diagnosis | prediction of medical events and evaluation of the prognosis | ANN | [44,45,46,47,48,49,50] | |
Obstetrics and gynecology | as a tool for FHR and CTG; the possibility of determining the most valid oocytes and embryos for pregnancy prediction using IVF | ANN, genetic algorithm | [51,52,53] |
3.2. The Use of Artificial Intelligence in Ophthalmology
3.2.1. Use of Neural Networks in Diabetic Retinopathy
3.2.2. Use of Neural Networks in Glaucoma
3.2.3. Use of Neural Networks in AMD
3.2.4. Use of Neural Networks in Retinopathy of Prematurity
3.2.5. Use of Neural Networks in Cataract and Other Pathology
4. Discussion and Perspectives
5. The Advantages and Limitations of Using Artificial Intelligence Tools
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Public Datasets | EYEPACS | ODIR | APTOS | DR 1 and 2 | IDRiD | Jichi | ROD Rep | Messidor 2 | Tsukazaki | PALM |
---|---|---|---|---|---|---|---|---|---|---|
Images | 88,702 | 8000 | 5590 | 1597 | 516 | 9939 | 1120 | 1748 | 13,047 | 1200 |
Country | USA | China | India | Brazil | India | Japan | Netherlands | France | Japan | China |
Grading DR Glaucoma Cataract others | ICDR no | ICDR yes | ICDR | None | ICDR | Mod Davis | Not specified | ICDR | None | Not applicable |
Sex, age, quality control, socio-economic aspects, or ethnicity | yes | yes | no | no | no | no | no | yes | yes | no |
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Anton, N.; Doroftei, B.; Curteanu, S.; Catãlin, L.; Ilie, O.-D.; Târcoveanu, F.; Bogdănici, C.M. Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions. Diagnostics 2023, 13, 100. https://doi.org/10.3390/diagnostics13010100
Anton N, Doroftei B, Curteanu S, Catãlin L, Ilie O-D, Târcoveanu F, Bogdănici CM. Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions. Diagnostics. 2023; 13(1):100. https://doi.org/10.3390/diagnostics13010100
Chicago/Turabian StyleAnton, Nicoleta, Bogdan Doroftei, Silvia Curteanu, Lisa Catãlin, Ovidiu-Dumitru Ilie, Filip Târcoveanu, and Camelia Margareta Bogdănici. 2023. "Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions" Diagnostics 13, no. 1: 100. https://doi.org/10.3390/diagnostics13010100