Postgraduate medical journal
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We aimed to develop an artificial intelligence (AI) model based on transrectal ultrasonography (TRUS) images of biopsy needle tract (BNT) tissues for predicting prostate cancer (PCa) and to compare the PCa diagnostic performance of the radiologist model and clinical model. ⋯ The proposed FPN model can offer a new method for prostate tissue classification, improve the diagnostic performance, and may be a helpful tool to guide prostate biopsy.
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The lack of transparency is a prevalent issue among the current machine-learning (ML) algorithms utilized for predicting mortality risk. Herein, we aimed to improve transparency by utilizing the latest ML explicable technology, SHapley Additive exPlanation (SHAP), to develop a predictive model for critically ill patients. ⋯ A transparent ML model for predicting outcomes in critically ill patients using SHAP methodology is feasible and effective. SHAP values significantly improve the explainability of ML models.
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Observational Study
Gastroesophageal reflux disease increases the risk of essential hypertension: results from the Nationwide Readmission Database and Mendelian randomization analysis.
The link between gastroesophageal reflux disease (GERD) and essential hypertension (EH) and its causal nature remains controversial. Our study examined the connection between GERD and the risk of hypertension and assessed further whether this correlation has a causal relationship. ⋯ GERD is a causal risk factor for EH. Further research is required to probe the mechanism underlying this causal connection.
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Generative conversational artificial intelligence (AI) has huge potential to improve medical education. This pilot study evaluated the possibility of using a 'no-code' generative AI solution to create 2D and 3D virtual avatars, that trainee doctors can interact with to simulate patient encounters. ⋯ By providing trainees with realistic scenarios, this technology allows trainees to practice answering patient questions regardless of actor availability, and indeed from home. Furthermore, the use of a 'no-code' platform allows clinicians to create customized training tools tailored to their medical specialties. While overall successful, this pilot study highlighted some of the current drawbacks and limitations of generative conversational AI, including the risk of outputting false information. Additional research and fine-tuning are required before generative conversational AI tools can act as a substitute for actors and peers.