Large-scale computation of pediatric growth percentiles with fuzzy logic justification of parameter selection

• Published in: 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) pp. 43 - 46
• Main Authors: Chengpeng Bi, Leeder, J. S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2012
• Subjects: Approximation methods; Biomedical measurements; Fuzzy logic; Gaussian distribution; Pediatric growth charts; Pediatrics; percentile; Weight measurement
• ISBN: 9781467311908; 1467311901
• DOI: 10.1109/CIBCB.2012.6217209

The electronic health record is now becoming a hot topic in the medical community largely owing to the rapid advances in both information technology and emerging personalized medicine. In pediatric research and clinical care, an important issue is to find the physical growth percentiles. Prior to the advent of electronic medical records, height and weight were measured and manually plotted on the growth charts for a rough estimate. In research, especially population studies, circumstances often arise that require large-scale clinical computation, which is not yet satisfactorily solved. This paper implements a fast approximate method to enable large-scale percentile computation available online. Additionally, the fuzzy logic approach is presented to justify the parameter selection.