Article citationsMore>>

Gennatas, E.D., Friedman, J.H., Ungar, L.H., Pirracchio, R., Eaton, E., Reichmann, L.G., et al. (2020) Expert-Augmented Machine Learning. Proceedings of the National Academy of Sciences, 117, 4571-4577.
https://doi.org/10.1073/pnas.1906831117

has been cited by the following article:

• TITLE: Modelling a Hybrid System: Deductive System and Machine Learning

  AUTHORS: Ahoua Cyrille Aka, Kra Lagasane Ouattara, Yapi Debarros Emmannuela, Konan Brou Marcellin

  KEYWORDS: Machine Learning, Expert System, Prediction, Modern Medicine, Hybrid System, Mathematical Model

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.15 No.11, October 31, 2025

  ABSTRACT: This research presents a mathematical model of medical decision support systems that combines the predictive approach of machine learning with the deductive approach of expert systems. This modeling has established an experimental framework highlighting various approaches to combining predictive and deductive systems. This framework allows for quantitative evaluation of the hybrid system’s performance, providing physicians with a transparent and quantifiable perspective on what they can expect. This model is not limited to being a technical tool; it also aims to strengthen practitioners’ confidence by providing both accuracy and transparent explanations.