Dr. Answer AI for prostate cancer: Clinical outcome prediction model and service.

OBJECTIVES: The importance of clinical outcome prediction models using artificial intelligence (AI) is being emphasized owing to the increasing necessity of developing a clinical decision support system (CDSS) employing AI. Therefore, in this study, we proposed a "Dr. Answer" AI software based on the clinical outcome prediction model for prostate cancer treated with radical prostatectomy. METHODS: The Dr. Answer AI was developed based on a clinical outcome prediction model, with a user-friendly interface. We used 7,128 clinical data of prostate cancer treated with radical prostatectomy from three hospitals. An outcome prediction model was developed to calculate the probability of occurrence of 1) tumor, node, and metastasis (TNM) staging, 2) extracapsular extension, 3) seminal vesicle invasion, and 4) lymph node metastasis. Random forest and k-nearest neighbors algorithms were used, and the proposed system was compared with previous algorithms. RESULTS: Random forest exhibited good performance for TNM staging (recall value: 76.98%), while k-nearest neighbors exhibited good performance for extracapsular extension, seminal vesicle invasion, and lymph node metastasis (80.24%, 98.67%, and 95.45%, respectively). The Dr. Answer AI software consisted of three primary service structures: 1) patient information, 2) clinical outcome prediction, and outcomes according to the National Comprehensive Cancer Network guideline. CONCLUSION: The proposed clinical outcome prediction model could function as an effective CDSS, supporting the decisions of the physicians, while enabling the patients to understand their treatment outcomes. The Dr. Answer AI software for prostate cancer helps the doctors to explain the treatment outcomes to the patients, allowing the patients to be more confident about their treatment plans.

Anti-Inflammatory and Antimicrobial Effects of a Novel Herbal Formulation (WSY-1075) in a Chronic Bacterial Prostatitis Rat Model.

PURPOSE: The aim of this study was to investigate the anti-inflammatory and anti-oxidative effects of a multi-herbal formula known as WSY-1075 in the treatment of chronic bacterial prostatitis in a rat model. MATERIALS AND METHODS: Experimental chronic bacterial prostatitis was induced in 32 Wistar rats by instillation of a bacterial suspension (Escherichia coli, 108 colony-forming units [CFU]/mL) into the prostatic urethra. After the induction of prostatitis, the rats were randomly divided into one of 4 treatment groups: control (n=8), ciprofloxacin (n=8), WSY-1075 (400 mg/kg) (n=8), and WSY-1075 (400 mg/kg)+ciprofloxacin (n=8). After 4 weeks of treatment, microbiological data from prostate tissue cultures, level of prostatic pro-inflammatory cytokines (tumor necrosis factor-α [TNF-α], interleukin [IL]-6, and IL-8), anti-oxidant effects (superoxide dismutase [SOD]), and histological findings were noted. RESULTS: The WSY-1075, ciprofloxacin, and WSY-1075+ciprofloxacin groups showed fewer CFUs in prostate tissue cultures than the control group. The WSY-1075, ciprofloxacin and WSY-1075+ciprofloxacin groups showed statistically significantly lower levels of the pro-inflammatory cytokines TNF-α, IL-6, and IL-8 than the control group. SOD levels in the WSY-1075, ciprofloxacin and WSY-1075+ciprofloxacin groups were significantly higher than in the control group. CONCLUSIONS: This study found that WSY-1075 had anti-microbial effects, anti-inflammatory effects, and anti-oxidative effects in a chronic bacterial prostatitis rat model. We expect the WSY-1075 may be useful for the clinical treatment of chronic bacterial prostatitis.