Development and validation of hybrid machine learning approach for predicting survival in patients with cervical cancer: a SEER-based population study

The hybrid model provides a promising tool for personalized risk stratification in cervical cancer based on survival probability. Further testing in varied clinical categories is recommended to confirm its efficiency in precision oncology.

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Publication Details

Journal
Frontiers in Oncology
Published
2025-06-18
DOI
https://doi.org/10.3389/fonc.2025.1605378
Citations
2
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
4.96
Controls
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article

Development and validation of hybrid machine learning approach for predicting survival in patients with cervical cancer: a SEER-based population study

B Venkataramana, Anjana Eledath Kolasseri
2 citations
Frontiers in Oncology
AI in cancer detection
4.96
article

Development and validation of hybrid machine learning approach for predicting survival in patients with cervical cancer: a SEER-based population study

B Venkataramana, Anjana Eledath Kolasseri
article en
2 citations

Abstract

The hybrid model provides a promising tool for personalized risk stratification in cervical cancer based on survival probability. Further testing in varied clinical categories is recommended to confirm its efficiency in precision oncology.

Frontiers in OncologyVol. 15
Vellore Institute of Technology University (IN)
Life in Land
Openalex Percentile: Top 5%
AI in cancer detection
4.96
DOIOpen Access PDFOpenAlex
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Development and validation of hybrid machine learning approach for predicting survival in patients with cervical cancer: a SEER-based population study — B Venkataramana, Anjana Eledath Kolasseri · Frontiers in Oncology (2025) | TGRS Research Map | TGRS