Fibrosis is a complex mechanism resulting from an abnormal deposit of extra-cellular matrix causing severe injuries or even a patient’s death from certain pathologies such as type C Hepatitis. Practitioners are able to predict the risk of their patients developing acute fibrosis.
We develop a portfolio of genetic algorithms for the prediction of acute fibrosis. These algorithms are essential to:
- The Patient
who knows his fibrosis risk and benefits from tailored treatment, increasing his/her chances of survival.
- The Practitioner
who identifies early patients at risk and makes enlightened treatment decisions, increasing efficiency of the prescribed regimen.
- Public Health Administrators and Health Insurers
optimizing their budgets because treatments are prescribed early and cases of acute fibrosis decrease.