[Use of artificial intelligence in geographic atrophy in age-related macular degeneration].
Petrus ChangLeon von der EmdeMaximilian PfauSandrine KünzelMonika FleckensteinSteffen Schmitz-ValckenbergFrank G HolzPublished in: Die Ophthalmologie (2024)
The first regulatory approval of treatment for geographic atrophy (GA) secondary to age-related macular degeneration in the USA constitutes an important milestone; however, due to the nature of GA as a non-acute, insidiously progressing pathology, the ophthalmologist faces specific challenges concerning risk stratification, making treatment decisions, monitoring of treatment and patient education. Innovative retinal imaging modalities, such as fundus autofluorescence (FAF) and optical coherence tomography (OCT) have enabled identification of typical morphological alterations in relation to GA, which are also suitable for the quantitative characterization of GA. Solutions based on artificial intelligence (AI) enable automated detection and quantification of GA-specific biomarkers on retinal imaging data, also retrospectively and over time. Moreover, AI solutions can be used for the diagnosis and segmentation of GA as well as the prediction of structure and function without and under GA treatment, thereby making a valuable contribution to treatment monitoring and the identification of high-risk patients and patient education. The integration of AI solutions into existing clinical processes and software systems enables the broad implementation of informed and personalized treatment of GA secondary to AMD.
Keyphrases
- artificial intelligence
- pet ct
- optical coherence tomography
- machine learning
- healthcare
- age related macular degeneration
- big data
- deep learning
- primary care
- high resolution
- combination therapy
- end stage renal disease
- chronic kidney disease
- newly diagnosed
- prognostic factors
- electronic health record
- data analysis
- photodynamic therapy
- acute respiratory distress syndrome
- respiratory failure
- single cell
- mechanical ventilation
- bioinformatics analysis