With the constant increase of multiple molecular data from genome-, proteome- transcriptome-wide studies become urgent the development of analytical tools that help scientists and clinician in the interpretation and practical application of these large amount of information. Thus algorithms that can select and combine multiple species of molecules, possibly derived from blood tests, may be of particular relevance for the near future development of translational research.
It becomes evident that Artificial Intelligence assumes a fundamental role for the improvement of techniques and analytical methods that will promote the transformation from the actual “generalized” medicine to personalized medicine. In this context, artificial neural networks, which use thousands of connected nodes to interpret data much like neurons in the brain and form the basis of machine learning, can process vast amounts of data and identify biomarker patterns associated with liver disease. In addition, by definition, machine learning is self-improving, thus as more data are put into the system, more its own algorithm is trained to improve its performances.
At the Italian Liver Foundation, we are developing tools to predict the development of chronic liver diseases, such as NASH/NAFLD (non-alcoholic steatohepatitis / Non-alcoholic fatty liver disease) and their progression to more severe stages, including the possible risk of tumor development. Artificial Intelligence combines multiple information derive from the analysis of different molecules to decipher weak signals from the biological source to identify population at risk for the development of very early disease and possibly predict the future progression
Early identify subjects at risk
Applying innovative Artificial Intelligence solutions to current clinical practice
With Hospitals and SME, public and private institutes
For the innovation in clinical hepatology