# Risk-stratification machine learning model using demographic factors, gynaecological symptoms and β-catenin for endometrial hyperplasia and carcinoma: a cross-sectional study
> Masadah R.

URL kanonis: https://discover.unhas.ac.id/publications/risk-stratification-machine-learning-model-using-demographic-factors-gynaecologi
Jurnal / Konferensi: BMC Women S Health
Tahun terbit: 2023
DOI: https://doi.org/10.1186/s12905-023-02790-6
ISSN: 14726874
Kuartil SJR: Q1
Citations: 2

## Authors
- Masadah R.

## Abstract
Risk stratification based on demographics, clinical symptoms, and β-catenin possesses a good performance in differentiating non-atypical hyperplasia with later stages.

## Keywords
- Medicine
- Carcinoma
- Endometrial cancer
- Body mass index
- Atypical hyperplasia
- Internal medicine
- Endometrial hyperplasia
- Odds ratio
- Grading (engineering)
- Hysterectomy
- Oncology
- Gastroenterology
- Gynecology
- Pathology
- Cancer
- Civil engineering
- Engineering

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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