Abstract
| Original language | English |
|---|---|
| Article number | 2406797 |
| Journal | Advanced Science |
| Volume | 12 |
| Issue number | 7 |
| Online published | 27 Dec 2024 |
| DOIs | |
| Publication status | Published - 17 Feb 2025 |
| Externally published | Yes |
Funding
The authors were grateful to the funding support from the Hong Kong Research Grants Council (project reference: GRF14216222, GRF14203821, GRF14204621, GRF14207121, GRF14207920, GRF14207419, GRF14203919, GRF14219922, N_CUHK407/16), the Marine Conservation Enhancement Fund (MCEF20108_L02), the Science, Technology, and Innovation Commission of Shenzhen Municipality (SGDX20220530111005039) and the Innovation and Technology Commission (project reference: GHX-004-18SZ). The authors would like to acknowledge Prof. Mingli You (School of Life Science and Technology, Xi'an Jiaotong University), Mr. Yucheng Wu and Dr. Mingkun Xu (Guangdong Institute of Intelligence Science and Technology, Zhuhai), Dr. Ronjie Zhao and Dr. Meng Yan (State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong, China), Dr. Guangyao Cheng, Ms. Tianle Wang, Mr. Syed Muhammad Tariq Abbasi, Mr. Minqing Zhang, Mr. Chenglang Yuan, Ms. Qingyue Dong, Mr. Shirui Zhao, Ms. Khadija BIBI, and Ms. Syeda Aimen Abbasi (Department of Biomedical Engineering, The Chinese University of Hong Kong) for their support in the project development.
Research Keywords
- deep-learning
- digital PCR
- droplet microfluidics
- nucleic acid quantification
- segment anything model
Publisher's Copyright Statement
- This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/
RGC Funding Information
- RGC-funded
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