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Data Mining in the Clinical Treatment of Cancer
The AF Institute utilises technology which can systematically sift through huge amounts of clinical data (big data), show correlations, identify trends and clarify cross-connections.
The algorithms for this were developed specifically for use in healthcare with real data. They are tailor-made, which is why they deliver excellent results. Individual development sets us apart from other approaches, which – put simply – only adapt existing codes.
The AF Institute’s artificial intelligence extracts knowledge that was previously obscure, hidden and unknown, simply because the sheer amount of existing data cannot be grasped without machine support.
By providing visually prepared samples of existing but de facto hidden knowledge, our dashboard can aid doctors and researchers in deriving new insights.
Within clinical cancer treatment, our technology shows which therapies work and which do not, which complications are to be expected and which course the disease is likely to take (hospital planning).
The technology developed for the AF Institute organizes, interprets and visualizes data at a rapid pace. This displays regularities (patterns), deviations and relationships. Redundant and unimportant information is hidden.
This gives the treating specialists an easy-to-use tool that opens up a new, clear view of diseases, especially cancer. By interpreting the data visualized in the dashboard, doctors and researchers can gain access to new perspectives on the course of the disease and the treatment.