Evidence map›Paper›PMID 41324706›Full record

ArticleAnalytical and bioanalytical chemistry2025

Application of surface-enhanced Raman scattering combined with artificial intelligence for multiplex detection of chemotherapeutic agents used in solid tumors.

Biqing Chen, Jiayin Gao, Haizhu Sun, Yinghan Zhao, Yan Liu, Xinpeng Lv, Xiaohong Qiu, Yang Li

Abstract read
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In one paragraph

Article in Analytical and bioanalytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Biqing ChenThe Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, 150081, People's Republic of China.
Jiayin GaoThe Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, 150081, People's Republic of China.
Haizhu SunThe Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, 150081, People's Republic of China.
Yinghan ZhaoThe Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, 150081, People's Republic of China.
Yan LiuThe Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, 150081, People's Republic of China.
Xinpeng LvThe Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, 150081, People's Republic of China. 904157262@qq.com.
Xiaohong QiuThe Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, 150081, People's Republic of China. qiuxiaohong@hrbmu.edu.cn.
Yang LiCollege of Pharmacy, Harbin Medical University, Harbin, Heilongjiang, 150081, People's Republic of China. liy@hrbmu.edu.cn.ORCID http://orcid.org/0000-0002-0677-3245

Funding

Natural Science Foundation of Heilongjiang Province PL2024H134
6 · The paper itself

Abstract

Chemotherapy remains a cornerstone in the treatment of multiple solid and gynecologic malignancies, including endometrial cancer, ovarian cancer, and breast cancer. Carboplatin, epirubicin, gemcitabine, paclitaxel, topotecan, and docetaxel are widely used in combination regimens; however, there is still a lack of sensitive, rapid, and multiplex technologies for real-time monitoring of chemotherapeutic drug concentrations. In this study, we developed a carboxyl-polyethylene glycol (PEG)-modified magnetite (Fe₃O₄@PEG) nanoplatform combined with artificial intelligence (AI)-driven spectral analysis to achieve ultra-sensitive and multiplex detection of six chemotherapeutic drugs. Fe₃O₄ nanoparticles were synthesized by co-precipitation and subsequently functionalized with carboxyl-PEG to enhance drug capture efficiency and resistance to matrix interference. Using a confocal Raman imaging system, SERS spectra of single and mixed drug systems were collected, and convolutional neural networks (CNNs) were employed for automated feature extraction and classification to enable qualitative and quantitative analysis. The constructed SERS platform achieved 10⁻⁷-10⁻⁸ milligrams per milliliter (mg/mL) detection limits for all six drugs in serum matrices, with classification accuracies exceeding 95% in multiplex mixtures. For improved quantitative accuracy and normalization, the 2078 cm⁻

Indexed as

Artificial intelligence (AI)Chemotherapeutic drug monitoringMultiplex detectionSurface-enhanced Raman scattering (SERS)

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.