What Does the Future Hold for Artificial Neural Networks?
Clinically, an artificial neural network would probably work as an interactive, Web-based tool. The physician would enter a patient’s treatment history, baseline CD4+ cell count, baseline viral load and the results of a genotype. The artificial neural network would then recommend the top 10 combinations of antiretroviral medications and the corresponding expected change in viral load for each. The clinician would then use these recommendations to select a new antiretroviral regimen. Artificial neural networks could also help select an optimized background medication when starting a new drug, such as tipranavir (TPV, Aptivus) or TMC114, that was not included in the treatment change episodes data sets. The artificial neural networks could be updated on a continuous basis by inputting more treatment change episodes that incorporate new agents and new combinations of agents. The artificial neural networks used in this study are being developed by a nonprofit British organization called the
