Park, Jihwan; Rho, Mi Jung; Moon, Hyong Woo; Kim, Jaewon; Lee, Chanjung; Kim, Dongbum; Kim, Choung-Soo; Jeon, Seong Soo; Kang, Minyong; Lee, Ji Youl
Technology in cancer research & treatment
2021Jan ; 20 ( 7 ) :15330338211024660.
PMID : 34180308
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Park, Jihwan -
Rho, Mi Jung -
Moon, Hyong Woo -
Kim, Jaewon -
Lee, Chanjung -
Kim, Dongbum -
Kim, Choung-Soo -
Jeon, Seong Soo -
Kang, Minyong -
Lee, Ji Youl -
ABSTRACT
Objectives: To develop a model to predict biochemical recurrence (BCR) after radical prostatectomy (RP), using artificial intelligence (AI) techniques.
Patients and methods: This study collected data from 7,128 patients with prostate cancer (PCa) who received RP at 3 tertiary hospitals. After preprocessing, we used the data of 6,755 cases to generate the BCR prediction model. There were 16 input variables with BCR as the outcome variable. We used a random forest to develop the model. Several sampling techniques were used to address class imbalances.
Results: We achieved good performance using a random forest with synthetic minority oversampling technique (SMOTE) using Tomek links, edited nearest neighbors (ENN), and random oversampling: accuracy = 96.59%, recall = 95.49%, precision = 97.66%, F1 score = 96.59%, and ROC AUC = 98.83%.
Conclusion: We developed a BCR prediction model for RP. The Dr. Answer AI project, which was developed based on our BCR prediction model, helps physicians and patients to make treatment decisions in the clinical follow-up process as a clinical decision support system.
keyword
Doctor¡¯s Answer; PROMISE CLIP registry; artificial intelligence; biochemical recurrence; prostate cancer; radical prostatectomy; random forest
MESH
Adult, Aged, Aged, 80 and over, Area Under Curve, *Artificial Intelligence, Decision Trees, Humans, Male, Middle Aged, *Models, Biological, Neoplasm Recurrence, Local/*blood, Prostate-Specific Antigen/blood, Prostatectomy, Prostatic Neoplasms/*blood/*pathology/surgery, ROC Curve, *Software
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