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Artificial intelligence (AI) for polymerase chain reaction (PCR): a state-of-the-art review

2026-06Artigo científico Acesso aberto
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datacite.subject.sdg03:Saúde de Qualidade
dc.contributor.authorAndaluz, Stephanie
dc.contributor.authorLv, Aman
dc.contributor.authorYu, Pengyu
dc.contributor.authorHui, Wenhao
dc.contributor.authorShen, Ren
dc.contributor.authorLiu, Tzu-Ming
dc.contributor.authorBrito, Miguel
dc.contributor.authorMak, Pui-In
dc.contributor.authorMartins, Rui P.
dc.contributor.authorJia, Yanwei
dc.date.accessioned2026-07-09T08:52:27Z
dc.date.available2026-07-09T08:52:27Z
dc.date.issued2026-06
dc.descriptionThis work is supported by the Macau Science and Technology Development Fund (FDCT) [FDCT0168/2023/RIA3, FDCT0001/2025/ RID, FDCT0213/2024/AGJ, FDCT0001/2025/NRP]; University of Macau [UMDF-TISF/2025/014/IME, SRG2024–00057-IME].
dc.description.abstractPolymerase chain reaction (PCR) and its advanced derivatives—quantitative PCR (qPCR), digital PCR (dPCR), high-resolution melting (HRM) analysis, and isothermal amplification—remain central to molecular diagnostics. Their growing data complexity demands computational solutions beyond traditional analysis. Meanwhile, the advancement of artificial intelligence (AI) algorithms has driven progress from conventional shallow machine learning (ML) to more complex deep learning approaches. Currently, AI is able to provide powerful frameworks for interpreting amplification dynamics, optimizing assay design, and visualizing molecular reactions in real time. With the assistance of AI, PCR can be transformed from a common laboratory technique into an intelligent diagnostic system. Herein, we review recent progress at the intersection of AI and PCR across biomedical and clinical domains. These studies demonstrate that AI-enhanced PCR platforms have significantly improved diagnostic accuracy, reproducibility, and analytical throughput, while simultaneously reducing operator dependency and cost. AI-enabled PCR is poised to become a cornerstone for next-generation, intelligent molecular diagnostics in medicine.eng
dc.description.sponsorshipThis work is supported by the Macau Science and Technology Development Fund (FDCT) [FDCT0168/2023/RIA3, FDCT0001/2025/ RID, FDCT0213/2024/AGJ, FDCT0001/2025/NRP]; University of Macau [UMDF-TISF/2025/014/IME, SRG2024–00057-IME].
dc.identifier.citationAndaluz S, Lv A, Yu P, Hui W, Shen R, Brito M, et al. Artificial intelligence (AI) for polymerase chain reaction (PCR): a state-of-the-art review. Biomed Instrum. 2026;2(2):100052.
dc.identifier.doi10.1016/j.bmi.2026.100052
dc.identifier.issn3050-5372
dc.identifier.urihttp://hdl.handle.net/10400.21/22967
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier BV
dc.relation.hasversionhttps://www.sciencedirect.com/science/article/pii/S3050537226000251
dc.relation.ispartofBiomedical Instrumentation
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectArtificial Intelligence
dc.subjectAI
dc.subjectMachine learning
dc.subjectPolymerase chain reaction
dc.subjectPCR
dc.subjectDNA detection
dc.subjectLiterature review
dc.titleArtificial intelligence (AI) for polymerase chain reaction (PCR): a state-of-the-art revieweng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue2
oaire.citation.startPage100052
oaire.citation.titleBiomedical Instrumentation
oaire.citation.volume2
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameBrito
person.givenNameMiguel
person.identifier.ciencia-id231F-F341-7E93
person.identifier.orcid0000-0001-6394-658X
person.identifier.ridA-7970-2016
person.identifier.scopus-author-id35224551000
relation.isAuthorOfPublication4252d8e0-800c-4d67-8b13-0b711d860669
relation.isAuthorOfPublication.latestForDiscovery4252d8e0-800c-4d67-8b13-0b711d860669

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