For most patients, a diagnosis of stage 4 non-small cell lung cancer comes with a dire prognosis. But for patients with specific mutations that cause the disease, there are potentially life-saving therapies.
The problem is that these mutations, known as ALK and EGFR, are not always identified in patients — meaning they never get the treatment.
A new study from the Fred Hutchinson Cancer Research Center in Seattle used machine learning to find these needle-in-a-haystack patients. The idea was to leverage cancer databases to see if patients were being tested for the mutations and receiving these personalized treatments.
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