Precision medicine is a medical paradigm in which treatments are customized entirely to the individual patient. The underlying issue that drives precision medicine is that for many complex diseases, there are no “one size fits all” solutions for patients with a particular diagnosis. The proper treatment for a patient depends upon genetic, environmental, and lifestyle choices. The ability to personalize treatment in a scientifically rigorous manner based on these factors is thus the hallmark of the emerging precision medicine paradigm. Nowhere is the potential impact of precision medicine more closely focused at the moment than in cancer, where lifesaving treatments for particular patients could prove ineffective or even deadly for other patients based entirely upon the particular genetic mutations in the patient’s tumor(s). Significant effort, therefore, has been devoted to deepening the scientific research surrounding precision medicine. This includes the Precision Medicine Initiative (Collins and Varmus, 2015) launched by President Barack Obama in 2015, now known as the All of Us Research Program. A fundamental difficulty with putting the findings of precision medicine into practice is that–by its very nature–precision medicine creates a very large space of treatment options (Frey et al., 2016). These can easily overwhelm clinicians attempting to stay up-to-date with the latest findings, and can easily inhibit a clinician’s attempts to determine the best possible treatment for a particular patient. However, the ability to quickly locate relevant evidence is the hallmark of information retrieval (IR). For three consecutive years the TREC Clinical Decision Support (CDS) track sought to evaluate IR
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