Machine learning predicts cancer origin and treatment response in cancer of unknown primary

A machinelearning classifier predicts origin of cancer of unknown primary based on electronicrecords and NGS data, showing that patients treated accordingly to model predictions had significantly better outcomes. DanaFarber broadinstitute

The participation of patients and the efforts of an institutional data collection system made this study possible, and we are grateful for their contributions. We would also like to express our appreciation to the DFCI Oncology Data Retrieval System and AACR Project GENIE team for their role in aggregating, managing and delivering the data used in this project.

I.M. and A.G. were supported by R01 CA227237, R01 CA244569 and grants from The Louis B. Mayer Foundation, The Doris Duke Charitable Foundation, The Phi Beta Psi Sorority and The Emerson Collective. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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