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Related Concept Videos

Glaucoma: Overview01:25

Glaucoma: Overview

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Glaucoma is an eye condition characterized by increased intraocular pressure that damages the retina and optic nerve, leading to irreversible blindness if left untreated. The human eye has various components, including the cornea, iris, pupil, lens, and optic nerve. Aqueous humor is secreted by the epithelium of the ciliary body in the posterior chamber and flows through the trabecular meshwork and canal of Schlemm, maintaining normal intraocular pressure. The trabecular meshwork and the canal...
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Angle Closure Glaucoma: Treatment01:28

Angle Closure Glaucoma: Treatment

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Angle-closure glaucoma, or closed-angle glaucoma, is an eye condition where the iris bulges out and blocks the iridocorneal angle, resulting in a buildup of aqueous humor and increased intraocular pressure. Immediate medical attention is necessary due to the sudden onset of symptoms. The treatment for angle-closure glaucoma includes short-term and long-term approaches. Short-term treatment involves using eye drops like pilocarpine to lower intraocular pressure by increasing aqueous humor...
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Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

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In open-angle glaucoma, the iridocorneal angle remains open, but the trabecular meshwork becomes stiff, slowing down the outflow of aqueous humor. This causes a buildup of aqueous humor in the anterior chamber, leading to a sudden increase in intraocular pressure. The treatment for open-angle glaucoma focuses on reducing the elevated intraocular pressure by either decreasing the secretion of aqueous humor or increasing its outflow.
Drugs such as carbonic anhydrase inhibitors, α2- and...
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Area of Science:

  • Artificial intelligence
  • Natural language processing
  • Healthcare informatics

Background:

  • Natural language processing (NLP) is a subset of artificial intelligence (AI) that enables computers to interpret human language.
  • NLP is in its early stages of development within the healthcare sector, presenting both opportunities and obstacles.
  • This review focuses on AI-driven NLP in healthcare and ophthalmology.

Purpose of the Study:

  • To provide an overview of AI-based NLP.
  • To explore its applications in healthcare and ophthalmology.
  • To discuss future use cases and deployment challenges.

Main Methods:

  • Literature review of AI-based NLP applications in healthcare.
  • Analysis of current and potential use cases in ophthalmology.
  • Identification of challenges and facilitators for NLP deployment.

Main Results:

  • AI-based NLP systems show promise for clinical applications like disease screening, risk stratification, and treatment monitoring.
  • Stakeholder collaboration, public acceptance, and technological progress are crucial for NLP's evolution in healthcare.
  • The integration of NLP into clinical workflows can enhance patient care.

Conclusions:

  • Patient-centric and personalized care are healthcare goals that AI-based NLP can support.
  • Addressing challenges through stakeholder collaboration is essential for large-scale NLP implementation.
  • Equitable and generalizable NLP systems can significantly benefit healthcare and society.