A study of health effects of long-distance ocean voyages on seamen using a data classification approach

Article (PDF Available)inBMC Medical Informatics and Decision Making 10(1):13 · March 2010with29 Reads
DOI: 10.1186/1472-6947-10-13 · Source: PubMed
Abstract
Long-distance ocean voyages may have substantial impacts on seamen's health, possibly causing malnutrition and other illness. Measures can possibly be taken to prevent such problems from happening through preparing special diet and making special precautions prior or during the sailing if a detailed understanding can be gained about what specific health effects such voyages may have on the seamen. We present a computational study on 200 seamen using 41 chemistry indicators measured on their blood samples collected before and after the sailing. Our computational study is done using a data classification approach with a support vector machine-based classifier in conjunction with feature selections using a recursive feature elimination procedure. Our analysis results suggest that among the 41 blood chemistry measures, nine are most likely to be affected during the sailing, which provide important clues about the specific effects of ocean voyage on seamen's health. The identification of the nine blood chemistry measures provides important clues about the effects of long-distance voyage on seamen's health. These findings will prove to be useful to guide in improving the living and working environment, as well as food preparation on ships.

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    • "Several other studies have provided alternative methods. For example, Support Vector Machine- Recursive Feature Elimination (SVM-RFE) was applied to train SVM for obtaining the weight of each feature and removing the one with the smallest weight iteratively7891011. This algorithm is superior to the ''naı¨venaı¨ve'' ranking with only one time RFE [7,12]. "
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