Training an Artificial Intelligence Model to Predict Breast Cancer Recurrence

Predicting cancer recurrence in patients with breast cancer is challenging. This study aimed to train and use an Artificial Intelligence (AI) model to predict breast cancer recurrence. The model successfully predicted recurrence versus no recurrence in 92.94% of patients. The three traits at presentation that correlated most to recurrence were positive ovarian status, negative human epidermal growth factor 2 receptor status, and negative estrogen receptor status. AI models can predict cancer recurrence and may become a useful tool in the management of cancer.

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Publication Details

Journal
Journal of Student Research
Published
2025-02-28
DOI
https://doi.org/10.47611/jsrhs.v14i1.8783
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Training an Artificial Intelligence Model to Predict Breast Cancer Recurrence

Anand Shah
1 links
Journal of Student Research
AI in cancer detection
article

Training an Artificial Intelligence Model to Predict Breast Cancer Recurrence

Anand Shah
article en

Abstract

Predicting cancer recurrence in patients with breast cancer is challenging. This study aimed to train and use an Artificial Intelligence (AI) model to predict breast cancer recurrence. The model successfully predicted recurrence versus no recurrence in 92.94% of patients. The three traits at presentation that correlated most to recurrence were positive ovarian status, negative human epidermal growth factor 2 receptor status, and negative estrogen receptor status. AI models can predict cancer recurrence and may become a useful tool in the management of cancer.

Journal of Student ResearchVol. 14(1)
Viewpoints Research Institute (US)
Openalex Percentile: Top 88%
AI in cancer detection
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