A Novel Approach to Glaucoma Screening using Computer Vision

Chakrabarty, Navoneel; Chatterjee, Subhrasankar

doi:10.1109/icssit46314.2019.8987803

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…Lastly, AI-based screening tools empower patients to actively engage in their health, offering timely information about their condition, facilitating informed decisions on treatment options, and encouraging regular monitoring for optimal eye health. In conclusion, leveraging artificial intelligence for the early detection of ocular diseases holds the potential to safeguard visual acuity, enhance treatment outcomes, reduce medical costs, and overall improve individual well-being by addressing ocular conditions before they advance to critical stages [8][9][10][11][12][13][14][15][16][17][18].…”

Section: Skin Pathologiesmentioning

confidence: 99%

Advancements in Healthcare: Development of a Comprehensive Medical Information System with Automated Classification for Ocular and Skin Pathologies—Structure, Functionalities, and Innovative Development Methods

Ștefan,

Rusu,

Ovreiu

et al. 2024

ASI

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This article introduces a groundbreaking medical information system developed in Salesforce, featuring an automated classification module for ocular and skin pathologies using Google Teachable Machine. Integrating cutting-edge technology with Salesforce’s robust capabilities, the system provides a comprehensive solution for medical practitioners. The article explores the system’s structure, emphasizing innovative functionalities that enhance diagnostic precision and streamline medical workflows. Methods used in development are discussed, offering insights into the integration of Google Teachable Machine into the Salesforce framework. This collaborative approach is a significant stride in intelligent pathology classification, advancing the field of medical information systems and fostering efficient healthcare practices.

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Section: Skin Pathologiesmentioning

confidence: 99%

Advancements in Healthcare: Development of a Comprehensive Medical Information System with Automated Classification for Ocular and Skin Pathologies—Structure, Functionalities, and Innovative Development Methods

Ștefan,

Rusu,

Ovreiu

et al. 2024

ASI

View full text Add to dashboard Cite

show abstract

“…In [84], the HRF database was used to test the DL-ML hybrid model for glaucoma screening in 30 images. The results reported an accuracy of 100% and a sensitivity of 1.0.…”

Section: Glaucoma Screeningmentioning

confidence: 99%

Literature Review on Artificial Intelligence Methods for Glaucoma Screening, Segmentation, and Classification

et al. 2022

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Artificial intelligence techniques are now being applied in different medical solutions ranging from disease screening to activity recognition and computer-aided diagnosis. The combination of computer science methods and medical knowledge facilitates and improves the accuracy of the different processes and tools. Inspired by these advances, this paper performs a literature review focused on state-of-the-art glaucoma screening, segmentation, and classification based on images of the papilla and excavation using deep learning techniques. These techniques have been shown to have high sensitivity and specificity in glaucoma screening based on papilla and excavation images. The automatic segmentation of the contours of the optic disc and the excavation then allows the identification and assessment of the glaucomatous disease’s progression. As a result, we verified whether deep learning techniques may be helpful in performing accurate and low-cost measurements related to glaucoma, which may promote patient empowerment and help medical doctors better monitor patients.

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Machine Learning Model Interpretability in NLP and Computer Vision Applications

Chakrabarty

2021

Communications in Computer and Information Science

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A Novel Approach to Glaucoma Screening using Computer Vision

Cited by 7 publications

References 6 publications

Advancements in Healthcare: Development of a Comprehensive Medical Information System with Automated Classification for Ocular and Skin Pathologies—Structure, Functionalities, and Innovative Development Methods

Advancements in Healthcare: Development of a Comprehensive Medical Information System with Automated Classification for Ocular and Skin Pathologies—Structure, Functionalities, and Innovative Development Methods

Literature Review on Artificial Intelligence Methods for Glaucoma Screening, Segmentation, and Classification

Machine Learning Model Interpretability in NLP and Computer Vision Applications

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