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Differentiating ChatGPT-Generated and Human-Written Medical Texts: Quantitative Study

December 30, 2023 No Comments

This study compares medical texts written by human experts with those generated by ChatGPT, revealing that while ChatGPT’s texts are fluent, they lack the specific, useful information typically found in human-authored texts. It also presents a machine learning method, with over 95% accuracy, for distinguishing between these two types of texts, underscoring the importance of responsible AI use in medicine.

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Supervised Machine Learning Model to Predict Mortality in Patients Undergoing Venovenous Extracorporeal Membrane Oxygenation from a Nationwide Multicentre Registry

December 29, 2023 No Comments

Machine learning models, specifically extreme gradient boosting and light gradient boosting, demonstrated higher accuracy than conventional models in predicting 90-day mortality for patients undergoing venovenous extracorporeal membrane oxygenation (VV-ECMO). These advanced models, outperforming existing methods like RESP and PRESERVE, show potential for improving patient selection by identifying those less likely to benefit from VV-ECMO therapy.

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Artificial Intelligence-Based Analysis of Body Composition Predicts Outcome in Patients Receiving Long-Term Mechanical Circulatory Support

December 28, 2023 No Comments

This study used artificial intelligence to analyze preoperative CT scans of heart failure patients receiving left ventricular assist device (LVAD) implantations, revealing that greater adipose tissue areas are associated with higher postoperative complications and in-hospital mortality. It concluded that preoperative body composition, particularly adipose tissue, can predict poorer outcomes post-LVAD implantation, impacting postoperative quality of life and walking distance.

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Organizational Factors in Clinical Data Sharing for Artificial Intelligence in Health Care

December 28, 2023 No Comments

This qualitative study explored organizational readiness for sharing health data for AI development across various sectors, finding that motivation and capabilities are central to data-sharing efforts. The study highlights that while organizational values align with data-sharing priorities, incentives can further enhance cross-sector collaborations and overcome barriers, suggesting tailored incentives may improve the sustainable flow of health data for AI development.

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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

December 25, 2023 No Comments

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

December 24, 2023 No Comments

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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