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1. Using Decision Tree Classification to Identify Cost Drivers of Hospitalization Expenses for Elderly Patients NSTL国家科技图书文献中心

Xiaojing Hu |  Yudian Liu... -  《Advances in Brain Inspired Cognitive Systems,Part I》 -  International Conference on Advances in Brain Inspired Cognitive Systems - 2025, - 62~71 - 共10页

摘要: undergoing laparoscopic surgery and to provide theoretical |  who underwent laparoscopic surgery between 2018 and |  regression decision tree model were employed to thoroughly |  decision tree model was further used to categorize |  surgical site. Using the decision tree model, with age
关键词: Decision tree |  Elderly patients |  Laparoscopic surgery |  Hospitalization costs

2. Study of Hospitalization for Knee Replacement Surgery: A Multicenter Study NSTL国家科技图书文献中心

Malta Rosaria Marino |  Giuseppe Longo... -  《6th International Conference on Biomedical Engineering》 -  International Conference on Biomedical Engineering - 2025, - 238~247 - 共10页

摘要:In modern medicine, knee replacement surgery |  risks as any surgery. Nowadays, the average (length of |  stay) LOS for knee replacement surgery can range from |  undergoing knee replacement surgery was evaluated using |  Learning (ML) models-Decision Tree (DT), Random Forest
关键词: Knee Replacement Surgery |  Multiple Linear Regression Analysis |  Machine Learning Algorithm |  Length of Stay

3. Use of Predictive Models to Analyze Hospitalization for Cardiovascular Interventions NSTL国家科技图书文献中心

Antonio D'Amore |  Gaetano D'Onofrio... -  《6th International Conference on Biomedical Engineering》 -  International Conference on Biomedical Engineering - 2025, - 357~363 - 共7页

摘要: percutaneous cardiovascular surgery. In this work were |  undergone a surgery on the cardiovascular system |  Forest algorithm, while for the Decision Tree algorithm | Cardiovascular disease remains the single most |  frequent cause of death among people over the age of 65
关键词: Machine Learning |  Length of Stay |  Cardiovascular Disease

4. Machine Learning for Improved Bariatric Surgery Management NSTL国家科技图书文献中心

Antonio D'Amore |  Gaetano D'Onofrio... -  《6th International Conference on Biomedical Engineering》 -  International Conference on Biomedical Engineering - 2025, - 345~354 - 共10页

摘要:Bariatric surgery has emerged as an effective |  following bariatric surgery using machine learning (ML |  from 757 patients undergoing bariatric surgery from |  Decision Tree (DT), Random Forest (RF), and Gradient |  treatment option for individuals with severe obesity
关键词: Bariatric Surgery |  Endocrinology |  Machine Learning

5. Role of Video Assisted Thoracoscopic Surgery (VATS) in the Management of Pulmonary Sequestration; A Meta-Analysis NSTL国家科技图书文献中心

Kakamad, Fahmi H. |  Amin, Bnar J. Hama... -  《Current respiratory medicine reviews》 - 2025,21(2) - 166~173 - 共8页

摘要: tissue without connection to the tracheobronchial tree |  thoracic surgery (VATS) in the management of pulmonary | , and outcomes of Video-Assisted Thoracoscopic Surgery |  Thoracoscopic Surgery for Pulmonary Sequestration and/or VATS | Background Pulmonary sequestration is a rare
关键词: Video assisted |  thoracoscopic surgery |  pulmonary sequestration |  birth defect |  lobectomy

6. The influence of preoperative fat distribution on post-bariatric surgery body mass index and body weight loss NSTL国家科技图书文献中心

Lu, Shi-jing |  Wang, Yan-yun... -  《Diabetes, obesity & metabolism.》 - 2025,27(4) - 1783~1791 - 共9页

摘要: bariatric surgery is a primary concern for both healthcare | , 2 and 5 years following surgery, were |  regressions, decision tree regressions and paired t tests to |  surgery, offering new insights into personalized weight | Background: The body weight following
关键词: abdominal fat |  bariatric surgery |  obesity |  subcutaneous fat |  weight loss

7. Magnitude Attention-based Dynamic Pruning NSTL国家科技图书文献中心

Jihye Back |  Namhyuk Ahn... -  《Expert Systems with Application》 - 2025,276(Jun.) - 126957.1~126957.11 - 共11页

摘要:Existing pruning methods often rely on weight |  Dynamic Pruning (MAP) method, which applies the |  but also outperform previous pruning methods on |  importance to identify sparse structures but typically |  apply this information statically, without leveraging
关键词: Model compression |  Model pruning |  Dynamic pruning |  Deep learning |  Optimization

8. Isomorphic Pruning for Vision Models NSTL国家科技图书文献中心

Gongfan Fang |  Xinyin Ma... -  《Computer Vision - ECCV 2024,Part XXX》 -  European Conference on Computer Vision - 2025, - 232~250 - 共19页

摘要:Structured pruning reduces the computational |  this, we present Isomorphic Pruning, a simple |  across different model sizes. Isomorphic Pruning |  pruning. Our empirical results on ImageNet-1K |  demonstrate that Isomorphic Pruning surpasses several
关键词: Network pruning |  Vision transformers |  CNNs

9. RePaIR: Repaired pruning at initialization resilience NSTL国家科技图书文献中心

Zhao, Haocheng |  Guan, Runwei... -  《Neural Networks》 - 2025,184 - Article 107086~Article 107086 - 共15页

摘要: application of neural network pruning. Unstructured pruning | . Unstructured Pruning at Initialization (PaI) optimizes the |  iterative pruning pipeline, but sparse weights increase |  obtaining the best pruning mask without considering | , and name it Repaired Pruning at Initialization
关键词: Pruning at initialization |  Lipschitz |  Neural network |  Unstructured pruning

10. Effective Layer Pruning Through Similarity Metric Perspective NSTL国家科技图书文献中心

Ian Pons |  Bruno Yamamoto... -  《Pattern Recognition,Part V》 -  International Conference on Pattern Recognition - 2025, - 423~438 - 共16页

摘要: demonstrated that pruning structures from these models is a |  filters. Studies have also been devoted to layer pruning | . However, layer pruning often hurts the network |  rates. This work introduces an effective layer-pruning |  pruning methods. Our method estimates the relative
关键词: Layer pruning |  Similarity metric |  Efficient deep learning
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