Coagulo-Net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks.

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Bibliographic Details
Title: Coagulo-Net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks.
Authors: Qian Y; School of Chemical, Materials and Biomedical Engineering, University of Georgia, Athens, USA., Zhu G; Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, USA., Zhang Z; Division of Applied Mathematics, Brown University, Providence, RI, USA., Modepalli S; School of Medicine, Georgetown University, Washington DC, USA., Zheng Y; Department of Mechanical and Material Engineering, Worcester Polytechnic Institute, Worcester, USA., Zheng X; Department of Mathematics, College of Information Science & Technology, Jinan University, Guangzhou, Guangdong, 510632, China., Frydman G; Division of Trauma, Emergency Surgery and Surgical Critical Care at the Massachusetts General Hospital, Boston, MA, USA; Division of Comparative Medicine, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA., Li H; School of Chemical, Materials and Biomedical Engineering, University of Georgia, Athens, USA. Electronic address: he.li3@uga.edu.
Source: Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2024 Dec; Vol. 180, pp. 106732. Date of Electronic Publication: 2024 Sep 19.
Publication Type: Journal Article
Journal Info: Publisher: Pergamon Press Country of Publication: United States NLM ID: 8805018 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-2782 (Electronic) Linking ISSN: 08936080 NLM ISO Abbreviation: Neural Netw Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-2782
DOI:10.1016/j.neunet.2024.106732