Artificial intelligence-based predictions in neovascular age-related macular degeneration.

Journal: Current opinion in ophthalmology

PMID: 34265783

Abstract

PURPOSE OF REVIEW: Predicting treatment response and optimizing treatment regimen in patients with neovascular age-related macular degeneration (nAMD) remains challenging. Artificial intelligence-based tools have the potential to increase confidence in clinical development of new therapeutics, facilitate individual prognostic predictions, and ultimately inform treatment decisions in clinical practice.

Authors

Daniela Ferrara

Genentech, Inc., South San Francisco, California.
Elizabeth M Newton

Genentech, Inc., South San Francisco, California.
Aaron Y Lee

Department of Ophthalmology, University of Washington, Seattle, Washington.

Keywords

Angiogenesis Inhibitors Artificial Intelligence Computer Simulation Fluorescein Angiography Humans Macular Degeneration Neovascularization, Pathologic Prognosis Receptors, Vascular Endothelial Growth Factor Tomography, Optical Coherence Vascular Endothelial Growth Factor A Wet Macular Degeneration

External Resources

View on PubMed Access via DOI PubMed (34265783)

Artificial intelligence-based predictions in neovascular age-related macular degeneration.

Abstract

Authors

Keywords

External Resources

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