A Comparative Study of Machine Learning Algorithms in Predicting Severe Complications after Bariatric Surgery
Explore this paper's citation graph
- Type
- preprint
- Published
- 2018-07-27
- Cited by
- 73
- References
- 62
- Access
- Open access
- OpenAlex
- https://openalex.org/W2883853320
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:92412900
Keywords
Algorithm, Machine learning, Artificial neural network, Surgery, Medicine
References
- Book Review: Computational Methods of Feature Selection
- Classification and Regression by randomForest
- Ensemble Methods: Foundations and Algorithms
- Peri-operative Safety in the Longitudinal Assessment of Bariatric Surgery
- Laparoscopic gastric bypass
- A study of the behavior of several methods for balancing machine learning training data
- Early Complications After Laparoscopic Gastric Bypass Surgery: Results From the Scandinavian Obesity Surgery Registry
- Risk Stratification Models: How Well do They Predict Adverse Outcomes in a Large Dutch Bariatric Cohort?
- Extremely randomized trees
- Development and validation of a bariatric surgery morbidity risk calculator using the prospective, multicenter NSQIP dataset.
- Predicting Risk for Serious Complications With Bariatric Surgery: Results from the Michigan Bariatric Surgery Collaborative
- Stochastic gradient boosting
- Risk stratification of serious adverse events after gastric bypass in the Bariatric Outcomes Longitudinal Database.
- A Model for Predicting the Resolution of Type 2 Diabetes in Severely Obese Subjects Following Roux-en Y Gastric Bypass Surgery
- Prognostic Bayesian networks: I: Rationale, learning procedure, and clinical use
- Indian Hedgehog: A Mechanotransduction Mediator in Condylar Cartilage
- Machine learning applications in cancer prognosis and prediction
- Intelligible Support Vector Machines for Diagnosis of Diabetes Mellitus
- The use of artificial neural networks in decision support in cancer: A systematic review
- Development of a decision tree to assess the severity and prognosis of stable COPD
Cited by
- Insights into Amyotrophic Lateral Sclerosis from a Machine Learning Perspective
- Prediction of Vestibular Dysfunction by Applying Machine Learning Algorithms to Postural Instability
- Anesthetic Agents and Cardiovascular Outcomes of Noncardiac Surgery after Coronary Stent Insertion
- Machine Learning Can Predict Deaths in Patients with Diverticulitis During their Hospital Stay
- Development and Evaluation of a Machine Learning Prediction Model for Flap Failure in Microvascular Breast Reconstruction
- The statistical importance of P-POSSUM scores for predicting mortality after emergency laparotomy in geriatric patients
- Comparative analysis of supervised machine learning algorithms for heart disease detection
- Deep Learning Neural Networks to Predict Serious Complications After Bariatric Surgery: Analysis of Scandinavian Obesity Surgery Registry Data
- In silico designing of peptide based vaccine for Hepatitis viruses using reverse vaccinology approach.
- Using Bayesian Networks to Predict Long-Term Health-Related Quality of Life and Comorbidity after Bariatric Surgery: A Study Based on the Scandinavian Obesity Surgery Registry
- A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit
- Predictive Value of Odor Identification for Incident Dementia: The Shanghai Aging Study
- Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysis
- Using a Convolutional Neural Network to Predict Remission of Diabetes After Gastric Bypass Surgery: Machine Learning Study From the Scandinavian Obesity Surgery Register
- Poor odor identification predicts mortality risk in older adults without neurodegenerative diseases: the Shanghai Aging Study
- Deus ex machina? Demystifying rather than deifying machine learning.
- Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients
- Adverse Outcomes Prediction for Congenital Heart Surgery: A Machine Learning Approach
- A Scoping Review of Artificial Intelligence and Machine Learning in Bariatric and Metabolic Surgery: Current Status and Future Perspectives
- The BAriatic surgery SUbstitution and nutrition (BASUN) population: a data-driven exploration of predictors for obesity
Related papers
- Remarks on Algorithm 2, Algorithm 3, Algorithm 15, Algorithm 25 and Algorithm 26
- Remarks on Algorithm 332: Jacobi polynomials: Algorithm 344: student's t-distribution: Algorithm 351: modified Romberg quadrature: Algorithm 359: factoral analysis of variance
- An improved filtering algorithm based on median filtering algorithm and medium filtering algorithm
- Remarks on algorithms 372 [A1]: An algorithm to produce complex primes, csieve and Algorithm 401 [A1]: an improved algorithm to produce complex primes
- A new algorithm for the detection of seismic quiescence: introduction of the RTM algorithm, a modified RTL algorithm
- Analysis on parameter sensitivity of distributed hydrological model based on LH-OAT Method
- Comparative assessment of the developed algorithm with the soft computing algorithm for the laser machined depth