Abstract
How can we predict the occurrence of acute kidney injury (AKI) in cancer patients based on machine learning with serum creatinine data? Given irregular and heterogeneous clinical data, how can we make the most of it for accurate AKI prediction? AKI is a common and significant complication in cancer patients, and correlates with substantial morbidity and mortality. Since no effective treatment for AKI still exists, it is important to take timely preventive measures. While several approaches have been proposed for predicting AKI, their scope and applicability are limited as they either assume regular data measured over a short hospital stay, or do not fully utilize heterogeneous data. In this paper, we provide an AKI prediction model with a greater applicability, which relaxes the constraints of existing approaches, and fully utilizes irregular and heterogeneous data for learning the model. In a cohort of 21,022 cancer patients who were registered into Korea Central Cancer Registry (KCCR) in Seoul National University Hospital between January 1, 2004 and December 31, 2013, our method achieves 0.7892 precision, 0.7506 recall, and 0.7576 F-measure in predicting whether a patient will develop AKI during the next 14 days.
Highlights
Acute kidney injury (AKI) is a common complication in cancer patients [1, 2]
The distribution of patients by cancer type is shown in Table 2: about 30% of the patients had respiratory tract cancer, and patients with respiratory tract cancer, gastrointestinal tract cancer, and thymus cancer comprised more than 60% of the total patients
While there exist several previous studies for predicting acute kidney injury (AKI), in this paper, we focus on developing an AKI prediction method with a high applicability that makes use of heterogeneous and irregular cancer patients’ data collected over a long period of time, with the goal of enabling better clinical decision making and AKI prevention
Summary
Acute kidney injury (AKI) is a common complication in cancer patients [1, 2]. A study on a cohort of 37,267 Danish cancer patients [3] reports that the 1-year and 5-year risk of AKI were 17.5% and 27.0%, respectively, with the 1-year risk increasing to 31.8% to 44.0% among patients with multiple myeloma, liver cancer, and kidney cancer. The Institute of Engineering Research at Seoul National University provided research facilities for this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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