An algorithm developed by researchers from Boston-based Dana-Farber Cancer Institute and Somerville, Mass.-based Mass General Brigham can predict a patient’s cancer risk based on genetic factors and clinical data found in the EHR.
The team trained the algorithm, called Aladynoulli, on 20 biological signatures with a high probability of initiating specific diseases and validated the algorithm on more than 683,000 patient records from three biobanks, according to a July 15 news release from Dana-Farber.
The signatures are “complex and overlapping” and allow the algorithm to predict the likelihood of a patient developing 348 distinct diseases, the release said.
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