iMIGS: An innovative AI based prediction system for selecting the best patient-specific glaucoma treatment

Qidwai, Uvais; Qidwai, Umair; Sivapalan, Thurka; Ratnarajan, Gokulan

doi:10.1016/j.mex.2023.102209

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…Qidwai et al [125] recently developed the Adaptive Neuro-Fuzzy Inference System (ANFIS), an AI algorithm that considers multiple baseline clinical parameters to suggest a specific minimally invasive glaucoma surgery (MIGS) treatment. They utilized a retrospective case series of patients who underwent one of four MIGS procedures to build a predictive model for the MIGS procedure using several baseline clinical characteristics.…”

Section: The Role Of Ai In Improving Glaucoma Outcomesmentioning

confidence: 99%

Advancing Glaucoma Care: Integrating Artificial Intelligence in Diagnosis, Management, and Progression Detection

Zhu,

Salowe,

Chow

et al. 2024

Bioengineering

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Glaucoma, the leading cause of irreversible blindness worldwide, comprises a group of progressive optic neuropathies requiring early detection and lifelong treatment to preserve vision. Artificial intelligence (AI) technologies are now demonstrating transformative potential across the spectrum of clinical glaucoma care. This review summarizes current capabilities, future outlooks, and practical translation considerations. For enhanced screening, algorithms analyzing retinal photographs and machine learning models synthesizing risk factors can identify high-risk patients needing diagnostic workup and close follow-up. To augment definitive diagnosis, deep learning techniques detect characteristic glaucomatous patterns by interpreting results from optical coherence tomography, visual field testing, fundus photography, and other ocular imaging. AI-powered platforms also enable continuous monitoring, with algorithms that analyze longitudinal data alerting physicians about rapid disease progression. By integrating predictive analytics with patient-specific parameters, AI can also guide precision medicine for individualized glaucoma treatment selections. Advances in robotic surgery and computer-based guidance demonstrate AI’s potential to improve surgical outcomes and surgical training. Beyond the clinic, AI chatbots and reminder systems could provide patient education and counseling to promote medication adherence. However, thoughtful approaches to clinical integration, usability, diversity, and ethical implications remain critical to successfully implementing these emerging technologies. This review highlights AI’s vast capabilities to transform glaucoma care while summarizing key achievements, future prospects, and practical considerations to progress from bench to bedside.

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Section: The Role Of Ai In Improving Glaucoma Outcomesmentioning

confidence: 99%

Advancing Glaucoma Care: Integrating Artificial Intelligence in Diagnosis, Management, and Progression Detection

Zhu,

Salowe,

Chow

et al. 2024

Bioengineering

View full text Add to dashboard Cite

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“…Selecting the optimal treatment strategy is complex, owing to the diverse factors unique to each patient. Decisions regarding treatment necessitate a deep understanding of underlying disease mechanisms and how various interventions alter ocular physiology [58][59][60]. AI may offer valuable assistance in this domain, enhancing surgical precision and predicting patient responses to treatments.…”

Section: Ai In Glaucoma Treatmentmentioning

confidence: 99%

“…Given the variability in patient responses due to individual characteristics, selecting the optimal MIGS approach presents a significant clinical challenge. However, one trial from the United Kingdom harnessed an Adaptive Neuro-Fuzzy Inference System (ANFIS) to navigate this complexity [58]. This system, designed to offer treatment recommendations, analyzed baseline clinical data-such as baseline demographics, IOP, VF scores, visual acuity, and glaucoma subtype-to guide ophthalmologists in choosing the most suitable MIGS procedure for each patient.…”

Section: Treatment Response Predictionmentioning

confidence: 99%

Artificial Intelligence in Glaucoma: A New Landscape of Diagnosis and Management

Ji,

Ramalingam,

Balas

et al. 2024

JCTO

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Glaucoma refers to a spectrum of progressive optic neuropathies and remains the leading cause of irreversible blindness worldwide. Its insidious onset poses serious challenges to conventional diagnostic methods and clinicians striving to detect early-stage disease for timely and effective intervention. Artificial intelligence (AI) has demonstrated its ability to process and analyze large datasets which can help identify subtle changes in early glaucomatous clinical presentation. This study reviews the current state of AI utilization in glaucoma and elucidates the strengths and limitations of existing approaches. We dissect the role of AI in various domains: enhancing early detection and diagnosis, monitoring disease progression, and refining treatment strategies to optimize patient outcomes. Furthermore, we address the ethical, legal, and social implications, alongside the inherent limitations of AI in the clinical setting. Despite these challenges, AI holds transformative potential for glaucoma management. Future directions emphasize the need for interdisciplinary collaboration, advanced and explainable algorithm development, and equitable healthcare access to fully realize the promise of AI in combating this vision-threatening condition.

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iMIGS: An innovative AI based prediction system for selecting the best patient-specific glaucoma treatment

Cited by 2 publications

References 17 publications

Advancing Glaucoma Care: Integrating Artificial Intelligence in Diagnosis, Management, and Progression Detection

Advancing Glaucoma Care: Integrating Artificial Intelligence in Diagnosis, Management, and Progression Detection

Artificial Intelligence in Glaucoma: A New Landscape of Diagnosis and Management

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