Machine learning-integrated electrochemical sensing of ciprofloxacin for digital point-of-care therapeutic drug monitoring.

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Bibliographic Details
Title: Machine learning-integrated electrochemical sensing of ciprofloxacin for digital point-of-care therapeutic drug monitoring.
Authors: Rajkumar C; Department of Electronic Engineering, Pukyong National University, Busan, 48513, South Korea.; School of Chemical Engineering, Yeungnam University, Gyeongsan, 38541, 280 Daehak-Ro, Republic of Korea., Mai ND; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, 48513, South Korea., Ramamoorthy S; Industry 4.0 Convergence of Bionics Engineering, Pukyong National University, Busan, 48513, South Korea., Shahid U; Industry 4.0 Convergence of Bionics Engineering, Pukyong National University, Busan, 48513, South Korea., Nkenyereye L; BK21; AI Convergence Education & Research Group, Pukyong National University, Busan, 48513, South Korea., Lim KT; Industry of display semiconductor technology, Pukyong National University, Busan, 48513, South Korea., Chung WY; Department of Electronic Engineering, Pukyong National University, Busan, 48513, South Korea. wychung@pknu.ac.kr., Oh TH; School of Chemical Engineering, Yeungnam University, Gyeongsan, 38541, 280 Daehak-Ro, Republic of Korea. taehwanoh@ynu.ac.kr.
Source: Mikrochimica acta [Mikrochim Acta] 2025 Dec 09; Vol. 193 (1), pp. 11. Date of Electronic Publication: 2025 Dec 09.
Publication Type: Journal Article
Journal Info: Publisher: Springer-Verlag Country of Publication: Austria NLM ID: 7808782 Publication Model: Electronic Cited Medium: Internet ISSN: 1436-5073 (Electronic) Linking ISSN: 00263672 NLM ISO Abbreviation: Mikrochim Acta Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1436-5073
DOI:10.1007/s00604-025-07722-9