Abstract
The general idea underlying Intrauterine Growth Curves (IGC) is simple and effective: fetuses grow up showing a regular trend, if they are too large or small for the gestational age, they are potentially pathologic and further exams are needed. Growth trends can be easily evaluated by means of ultrasound scanners, but no single standard, from literature or from practitioners’ organizations, seems to satisfy the desired requirements of precision and accuracy. On the contrary, failure rates as high as 50% are achieved. The problem is that several patient-related factors, such as ethnic group, food, sex (of fetus), drugs and smoke, must be taken into account to select the “right” IGC. In this perspective, starting from the quantitative comparison of growth trends from literature, we propose a collaborative approach and an online system to create personalized IGCs. The approach is tested on real patients and the preliminary results are discussed.
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Bochicchio, M.A., Vaira, L., Longo, A., Malvasi, A., Tinelli, A. (2014). Quantitative Fetal Growth Curves Comparison: A Collaborative Approach. In: Bursa, M., Khuri, S., Renda, M.E. (eds) Information Technology in Bio- and Medical Informatics. ITBAM 2014. Lecture Notes in Computer Science, vol 8649. Springer, Cham. https://doi.org/10.1007/978-3-319-10265-8_5
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DOI: https://doi.org/10.1007/978-3-319-10265-8_5
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