Abstract
The goal of our presentation is to predict functional outcome of operated Proximal Humeral Fractures by means of Artificial Neural Networks, so that we can compare anticipated results to real results recorded during scheduled follow-ups. We get the chance to assess above-mentioned method’s reliability as a proper tool in our daily practice and to analyze it in details in order to improve it.
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Acknowledgment
The authors are grateful for the support provided by the Bulgarian Ministry of Education and Science under the National Research Programme “Information and Communication Technologies for a Digital Single Market in Science, Education and Security” approved by DCM # 577/ 17.08.2018.
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Hristov, S., Baltov, A., Sotirov, S. (2022). Functional Outcome Prediction of Operated Proximal Humerus Fractures by Means of Artificial Neural Networks. In: Sotirov, S.S., Pencheva, T., Kacprzyk, J., Atanassov, K.T., Sotirova, E., Staneva, G. (eds) Contemporary Methods in Bioinformatics and Biomedicine and Their Applications. BioInfoMed 2020. Lecture Notes in Networks and Systems, vol 374. Springer, Cham. https://doi.org/10.1007/978-3-030-96638-6_23
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DOI: https://doi.org/10.1007/978-3-030-96638-6_23
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