CellWell record HH-539499
Predicting Prostate Cancer Risk and Its Associated Factors Using Machine Learning Techniques: A Retrospective Study
Serveh Mohammadi; Behzad Imani; Soheila Saeedi; Mohammad Ali Amirzargar
2026
In plain language
In a retrospective study of 597 medical records in Iran, an XGBoost machine learning model predicted prostate cancer with 77.5% accuracy, with PSA levels, hemoglobin, BMI, and fish consumption among key predictors.
- Evidence
- Emerging
- Design
- Primary research (design unspecified)
Cite this record: https://thecellwell.org/studies/HH-539499
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