Flemboda artificial intelligence: hybrid fuzzy-convolutional neural network for efficient chromosome abnormality classification

K. Kiruthika, S. Sarumathi, M. Karpagam, K. Kaviarasu

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DOI: 10.1007/s00438-025-02345-4
Published: 2026-01-21
Container: Molecular Genetics and Genomics
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s00438-025-02345-4,
  title = {Flemboda artificial intelligence: hybrid fuzzy-convolutional neural network for efficient chromosome abnormality classification},
  author = {K. Kiruthika and S. Sarumathi and M. Karpagam and K. Kaviarasu},
  year = {2026},
  journal = {Molecular Genetics and Genomics},
  doi = {10.1007/s00438-025-02345-4},
  url = {https://doi.org/10.1007/s00438-025-02345-4}
}

RIS

TY  - JOUR
TI  - Flemboda artificial intelligence: hybrid fuzzy-convolutional neural network for efficient chromosome abnormality classification
AU  - K. Kiruthika
AU  - S. Sarumathi
AU  - M. Karpagam
AU  - K. Kaviarasu
PY  - 2026
JO  - Molecular Genetics and Genomics
DO  - 10.1007/s00438-025-02345-4
UR  - https://doi.org/10.1007/s00438-025-02345-4
ER  -

APA

Kiruthika, K., Sarumathi, S., Karpagam, M., & Kaviarasu, K. (2026). Flemboda artificial intelligence: hybrid fuzzy-convolutional neural network for efficient chromosome abnormality classification. Molecular Genetics and Genomics. https://doi.org/10.1007/s00438-025-02345-4

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crossref · retrieved 2026-09-26T03:22:15.478Z