The Hill-RBF Calculator is an advanced, self-validating method for IOL power selection employing pattern recognition and sophisticated data interpolation. It has been optimized for use with the Haag-Streit Lenstar, using optical biometry for all axial measurements and high density autokeratometry.
Radial basis function IOL power selection performs the same for short, normal and long eyes. Based in artificial intelligence, this methodology is entirely data driven and free of calculation bias. This approach also employs a validating boundary model, indicating when it is performing within a defined area of accuracy.
The fundamental advantage of pattern recognition for selecting an IOL power is achieved through the process of adaptive learning - the ability to learn tasks based solely on data, independent of what is previously known. Current methods limit possibilities to situations that are already understood. This method is also self-organizing, meaning that it has the ability to create its own organization, or representation of data. Such an approach is well-suited to the complex, non-linear relationships that make up many aspects of the human eye.
Unlike static theoretical formulas, this approach will be an ongoing project and continuously updated as "big data" exercise. The greater the number of surgical outcomes that are fit to the RBF model, the greater the overall depth of accuracy. In it's preset form, the Hill-RBF Calculator has been optimized for biconvex IOLs from +6.00 D to +30.00 D.
The Hill-RBF method is now part of the Haag-Streit LENSTAR EyeSuite biometry software.