Assessing bioartificial organ function: the 3P model framework and its validation

Author:

An Jingmin123,Zhang Shuyu12,Wu Juan124,Chen Haolin124,Xu Guoshi124,Hou Yifan124,Liu Ruoyu12,Li Na5,Cui Wenjuan54,Li Xin124,Du Yi54,Gu Qi124ORCID

Affiliation:

1. Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, The State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chaoyang District, Beijing, 100101, P. R. China

2. Beijing Institute for Stem Cell and Regenerative Medicine, Chaoyang District, Beijing, 100101, P. R. China

3. Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, P. R. China

4. University of Chinese Academy of Sciences, Huairou District, Beijing, 100149, P. R. China

5. Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100864, P.R. China

Abstract

The 3P framework for liver models utilizes machine learning to enhance precision, personalization, and prediction in assessing liver functions, representing a significant advancement in the field of bioartificial organ research.

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

National Key Research and Development Program of China

Chinese Academy of Sciences

Publisher

Royal Society of Chemistry (RSC)

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