Mandala Sciences (MSI) CODA project has 2 main objectives: (1) develop analysis tools to test hypotheses regarding effectiveness of surgical procedures and patient outcomes and (2) generate proprietary decision support prediction models for hip and knee replacements. MSI hybrid Neural Network/Expert System methodology uses an Entropy NN TM structure which has the innovative ability to generate a rule base. The discovered rules will be used to create """"""""portable"""""""" Expert System predictive modules. Phase II progress is built upon successful MSI collaboration with Henry Ford Health System to show NN techniques can generate and evaluate prognostic models using outcomes data. Consultation with orthopedic surgeons identified 13 patient-provided variables as potential predictors of hip replacement surgery failure. An NN trained on these data predicted the 1-year post-surgical change in the patient's self-assessed pain and physical function scores. Comparison with standard statistical analysis techniques showed superior accuracy of NN-based predictions. Phase II research will generalize the product by adopting the ASTM-E-1238 interface standard for data collection from multiple sources. NN/Expert prediction models will be improved by pooling data from geographically diverse sites and field trial performance to evaluate physician-rated adoption, usefulness, and influence on their actual decision making.
MSI will build a user-friendly, stand-alone outcomes database analysis tool. By using new proprietary neural network techniques, the system will have the predictive power of NN combined with the explanatory capabilities of an expert system. This computer system will be adopted by the widest possible audience because it will be far easier to use than conventional statistical packages, and by virtue of being designed for compatibility with the ASTM-E-1238 standard for outcomes data transmission.
