Data-driven prediction of CIMS signal intensity for pesticide detection via dibromomethane reagent using machine learning techniques

Chaoqun Wen, Shaxnoza Saydaxmetova, Suranjana V. Mayani, Suhas Ballal, Harshit Gupta, Subhashree Ray, Aashna Sinha, Vikasdeep Singh Mann, Ahamad Alewedee, Issa Mohammed Kadhim, Aseel Smerat, Zarghuna Hekmatyar

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DOI: 10.1177/14690667251411711
Published: 2026-02
Container: European Journal of Mass Spectrometry
Publisher: SAGE Publications
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1177/14690667251411711,
  title = {Data-driven prediction of CIMS signal intensity for pesticide detection via dibromomethane reagent using machine learning techniques},
  author = {Chaoqun Wen and Shaxnoza Saydaxmetova and Suranjana V. Mayani and Suhas Ballal and Harshit Gupta and Subhashree Ray and Aashna Sinha and Vikasdeep Singh Mann and Ahamad Alewedee and Issa Mohammed Kadhim and Aseel Smerat and Zarghuna Hekmatyar},
  year = {2026},
  journal = {European Journal of Mass Spectrometry},
  doi = {10.1177/14690667251411711},
  url = {https://doi.org/10.1177/14690667251411711}
}

RIS

TY  - JOUR
TI  - Data-driven prediction of CIMS signal intensity for pesticide detection via dibromomethane reagent using machine learning techniques
AU  - Chaoqun Wen
AU  - Shaxnoza Saydaxmetova
AU  - Suranjana V. Mayani
AU  - Suhas Ballal
AU  - Harshit Gupta
AU  - Subhashree Ray
AU  - Aashna Sinha
AU  - Vikasdeep Singh Mann
AU  - Ahamad Alewedee
AU  - Issa Mohammed Kadhim
AU  - Aseel Smerat
AU  - Zarghuna Hekmatyar
PY  - 2026
JO  - European Journal of Mass Spectrometry
DO  - 10.1177/14690667251411711
UR  - https://doi.org/10.1177/14690667251411711
ER  -

APA

Wen, C., Saydaxmetova, S., Mayani, S. V., Ballal, S., Gupta, H., Ray, S., Sinha, A., Mann, V. S., Alewedee, A., Kadhim, I. M., Smerat, A., & Hekmatyar, Z. (2026). Data-driven prediction of CIMS signal intensity for pesticide detection via dibromomethane reagent using machine learning techniques. European Journal of Mass Spectrometry. https://doi.org/10.1177/14690667251411711

Source records

crossref · retrieved 2026-09-25T19:29:32.342Z