International Perfusion Association

Category: Artificial Intelligence

Machine Learning AKI

Incorporating Intraoperative Blood Pressure Time-Series Variables to Assist in Prediction of Acute Kidney Injury After Type A Acute Aortic Dissection Repair: An Interpretable Machine Learning Model

This study developed an XGBoost machine learning model using intraoperative blood pressure time-series data to predict the risk of acute kidney injury (AKI) after Type A acute aortic dissection repair. The model, which outperformed others in accuracy, identified factors like intraoperative urine output and the duration of mean arterial pressure below 65 mmHg as critical predictors for postoperative AKI.

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Chat GTP4 Xmas

Role of Generative Artificial Intelligence in Publishing. What is Acceptable, What is Not

Generative Artificial Intelligence (AI), including platforms like ChatGPT, is increasingly used in the scientific publishing world for tasks ranging from improving the quality of manuscripts to aiding in peer review processes. However, its use raises ethical concerns, such as potential cheating by students, breach of confidentiality by peer reviewers, and the opacity of AI systems, leading to calls for transparency and accountability in the use of AI in scientific publications, as well as guidelines for authors, reviewers, and publishers in declaring AI-generated content.

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