Medicine and HealthScientific Reports
Predictive modeling of proliferative vitreoretinopathy using automated machine learning by ophthalmologists without coding experience
F. Antaki, G. Kahwati, et al.
This study demonstrates that ophthalmologists, even without coding experience, can design machine learning algorithms to predict proliferative vitreoretinopathy (PVR) using automated ML techniques. Conducted by experts including Fares Antaki, Ghofril Kahwati, and Julia Sebag, the research revealed promising results with an AUC of 0.90 for PVR prediction. Explore how non-coding professionals can tap into the power of machine learning in ophthalmology!
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