AIMC Topic: Postoperative Complications
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Development and validation of a nomogram model to predict postoperative delirium after resection of esophageal cancer.
Scientific reports
Jul 21, 2025
The study aimed to establish and validate a nomogram model to predict postoperative delirium (POD) among esophageal cancer resection patients. Clinical data of 396 patients with esophageal cancer who underwent esophagectomy from November 2020 to June...
Development of a machine learning-derived model to predict unplanned ICU admissions after major non-cardiac surgery.
BMC anesthesiology
Jul 17, 2025
BACKGROUND: Unplanned postoperative intensive care unit admissions (UIAs) are rare events that cause significant challenges to perioperative workflow. We describe the development of a machine-learning derived model to predict UIAs using only widely u...
Imaging analysis using Artificial Intelligence to predict outcomes after endovascular aortic aneurysm repair: protocol for a retrospective cohort study.
BMJ open
Jul 16, 2025
INTRODUCTION: Endovascular aortic aneurysm repair (EVAR) requires long-term surveillance to detect and treat postoperative complications. However, prediction models to optimise follow-up strategies are still lacking. The primary objective of this stu...
Using machine learning algorithms to predict risk factors of heart failure after complete mesocolic excision in colorectal cancer patients.
Scientific reports
Jul 15, 2025
Following complete mesocolic excision (CME), heart failure (HF) emerges as a significant complication, exerting substantial impacts on both short-term and long-term patient prognoses. The primary objective of our investigation was to develop a machin...
Machine learning-based prediction model for post-ERCP cholangitis in patients with malignant biliary obstruction: a retrospective multicenter study.
Surgical endoscopy
Jul 9, 2025
BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is the preferred palliative treatment for patients with unresectable malignant biliary obstruction (MBO), which can relieve biliary obstruction and prolong survival. Post-ERCP cholangi...
Assessing the Accuracy of ChatGPT in Appropriately Triaging Common Postoperative Concerns Regarding Mohs Micrographic Surgery.
JMIR dermatology
Jul 8, 2025
Artificial intelligence (AI) is increasingly integrated into health care, offering potential benefits in patient education, triage, and administrative efficiency. This study evaluates AI-driven dialogue interfaces within an electronic health record a...
Fairness of machine learning readmission predictions following open ventral hernia repair.
Surgical endoscopy
Jul 7, 2025
INTRODUCTION: Few models have predicted readmission following open ventral hernia repair (VHR), and none have assessed fairness. Fairness evaluation assesses whether predictive performance is similar across demographic groups, ensuring that biases ar...
Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.
Renal failure
Jul 3, 2025
Kidney transplantation (KT) is an effective treatment for end-stage renal disease; however, the lifelong immunosuppressive regimen increases the risk of infection, presenting significant clinical, and economic challenges. Identifying predictive bioma...
Machine learning algorithms for prediction of cerebrospinal fluid leakage after posterior surgery for thoracic ossification of the ligamentum flavum.
Scientific reports
Jul 3, 2025
To develop and validate a machine-learning (ML) model that pre-operatively predicts cerebrospinal-fluid leakage (CSFL) after posterior decompression for thoracic ossification of the ligamentum flavum (TOLF), and to elucidate the key risk factors driv...
Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.
Scientific reports
Jul 1, 2025
Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elevate mortality rates. Consequently, early prevention and identification of this condition are crucial...
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