Artificial intelligence with Hill-RBF
IOL data from all over the world collected by leading cataract surgeons is the foundation for the Hill-RBF. This big data is analyzed by pattern recognition based on artificial intelligence leading to highly accurate IOL predictions and providing confidence thanks to a unique reliability check.
The new version of RBF is based on a bigger dataset consisting over 3x the amount of data compared to the previous version. This leads to an impressive outcome of 94.8% within ±0.5 D in all eyes. In addition the Hill-RBF was complemented with the well-established Abulafia-Koch algorithm for torical applications.
It is a pleasure to inform you about a new innovation in IOL calculation, the introduction of the Hill RBF 2.0 Method.
The RBF is a purely data driven IOL calculation method incorporating artificial intelligence, pattern recognition and a boundary model for improved accuracy and confidence.
RBF stands for Radial Basis Function, which is like a neural Network, specialised in feature extraction and feature recognition and can handle multiple factors and non-linear relationships.
The Hill-RBF Method performs as good and in short eyes even better than the best currently available theoretical formulae and it tells the user when a calculation is accurate and when care should be taken because of biometry parameters that do not allow accurate IOL prediction.
The new Hill-RBF Calculator Version 2.0 - IOL Power Calculations for Cataract Surgery is going to be available on-line as of the 8th NHG Eye Institute International Ophthalmology Congress 2018 will be held at Max Atria, Singapore Expo from 5 to 6 October 2018.