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A Predictive Method for Unplanned Postoperative Readmission Risk Based on Heterogeneous Data
Published 2025-01-01“…To address these issues, it is proposed to use machine learning technology combined with patient clinical heterogeneous data to develop a predictive model for unplanned postoperative readmission. …”
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Federated Learning for Predicting Major Postoperative Complications
Published 2025-06-01“…Conclusions:. We show federated learning to be a useful tool to train robust postoperative outcome prediction models from large-scale data across 2 hospitals.…”
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Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach
Published 2025-01-01“…MethodsThe iHurt study was conducted on 25 postoperative patients at the University of California, Irvine Medical Center. …”
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Development and validation of interpretable machine learning models for postoperative pneumonia prediction
Published 2024-12-01“…This study aimed to develop and validate a predictive model for postoperative pneumonia in surgical patients using nine machine learning methods.ObjectiveOur study aims to develop and validate a predictive model for POP in surgical patients using nine machine learning algorithms. …”
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Predicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning
Published 2025-03-01“…Moreover, the feature-reduced model showed an AUROC value of 0.785 for predicting the MCID of postoperative JOA in the external dataset, which included 58 patients from other hospitals.ConclusionWe developed models based on machine learning to predict postoperative neurological outcomes. …”
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Predicting postoperative pulmonary infection risk in patients with diabetes using machine learning
Published 2024-12-01“…BackgroundPatients with diabetes face an increased risk of postoperative pulmonary infection (PPI). However, precise predictive models specific to this patient group are lacking.ObjectiveTo develop and validate a machine learning model for predicting PPI risk in patients with diabetes.MethodsThis retrospective study enrolled 1,269 patients with diabetes who underwent elective non-cardiac, non-neurological surgeries at our institution from January 2020 to December 2023. …”
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Machine learning-based prediction of postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy
Published 2025-04-01“…Abstract Background Clinically relevant postoperative pancreatic fistula (CR-POPF) following laparoscopic pancreaticoduodenectomy (LPD) is a critical complication that significantly worsens patient outcomes. …”
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Postoperative Apnea‐Hypopnea Index Prediction of Velopharyngeal Surgery Based on Machine Learning
Published 2025-01-01“…Abstract Objective To investigate machine learning‐based regression models to predict the postoperative apnea‐hypopnea index (AHI) for evaluating the outcome of velopharyngeal surgery in adult obstructive sleep apnea (OSA) subjects. …”
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Prediction of postoperative vault after implantable collamer lens implantation with deep learning
Published 2025-07-01“…CONCLUSION: AI effectively predicts postoperative vault and determines ICL size. XGBoost outperforms other machine-learning algorithms tested. …”
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Predicting postoperative nausea and vomiting using machine learning: a model development and validation study
Published 2025-03-01“…Abstract Background Postoperative nausea and vomiting (PONV) is a frequently observed complication in patients undergoing surgery under general anesthesia. …”
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Machine Learning-Based Prediction of Postoperative Deep Vein Thrombosis Following Tibial Fracture Surgery
Published 2025-07-01“…<b>Background/Objectives</b>: Postoperative deep vein thrombosis (DVT) is a common and serious complication after tibial fracture surgery. …”
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Predicting postoperative complications after pneumonectomy using machine learning: a 10-year study
Published 2025-12-01“…Background Reducing postoperative cardiovascular and neurological complications (PCNC) during thoracic surgery is the key to improving postoperative survival.Objective We aimed to investigate independent predictors of PCNC, develop machine learning models, and construct a predictive nomogram for PCNC in patients undergoing thoracic surgery for lung cancer.Methods This study used data from a previous retrospective study of 16,368 patients with lung cancer (training set: 11,458; validation set: 4,910) with American Standards Association physical statuses I–IV who underwent surgery. …”
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Machine learning and the nomogram as the accurate tools for predicting postoperative malnutrition risk in esophageal cancer patients
Published 2025-06-01“…This study aimed to develop and validate predictive models using machine learning algorithms and a nomogram to estimate the risk of malnutrition at 1 month after esophagectomy.MethodsA total of 1,693 patients who underwent curative esophageal cancer surgery were analyzed, with 1,251 patients allocated to the development cohort and 442 to the validation cohort. …”
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Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip Fracture
Published 2025-02-01“…This model can serve as a useful tool to identify postoperative pneumonia and guide clinical strategies for super-aged patients with hip fracture.Keywords: machine learning, postoperative pneumonia, hip fracture, super-aged patients, geriatric patients…”
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AN INTELLIGENT POSTOPERATIVE CHRONIC PAIN PREDICTION SYSTEM (I-POCPP)
Published 2022-07-01“…The aim of this study is to predict the POCP status of patients based on perioperative data by developing an “Intelligent POCP Prediction System (I-POCPP)” using the best performing machine learning algorithm. Material and Method: The dataset for this multi-centered study was collected from 5 tertiary hospitals in Turkey and included 733 patients who had undergone elective surgeries attended by an anesthesiologist in the operating room. …”
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Machine learning models for diagnosing lymph node recurrence in postoperative PTC patients: a radiomic analysis
Published 2025-08-01“…This study aimed to explore the diagnostic capabilities of computed tomography (CT) imaging and radiomic analysis to distinguish the recurrence of cervical lymph nodes in patients with PTC postoperatively. Materials and methods A retrospective analysis of 194 PTC patients who underwent total thyroidectomy was conducted, with 98 cases of cervical lymph node recurrence and 96 cases without recurrence. …”
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Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer
Published 2025-02-01“…Abstract Background Gastric cancer patients are prone to lower extremity deep vein thrombosis (DVT) after surgery, which is an important cause of death in postoperative patients. Therefore, it is particularly important to find a suitable way to predict the risk of postoperative occurrence of DVT in GC patients. …”
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Predicting the risk of postoperative avascular necrosis in patients with talar fractures based on an interpretable machine learning model
Published 2025-07-01“…PurposeThis study aims to develop and validate an interpretable machine learning model for predicting avascular necrosis (AVN) following talar fracture, thereby aiding in personalized prevention and treatment.MethodsA retrospective cohort study included patients undergoing surgical intervention for talar fractures at Ningbo No.6 Hospital between January 2018 and December 2023. …”
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