Cargando…

A Machine Learning Approach to Predicting Diabetes Complications

Diabetes mellitus (DM) is a chronic disease that is considered to be life-threatening. It can affect any part of the body over time, resulting in serious complications such as nephropathy, neuropathy, and retinopathy. In this work, several supervised classification algorithms were applied for buildi...

Descripción completa

Detalles Bibliográficos
Autores principales:	Jian, Yazan, Pasquier, Michel, Sagahyroon, Assim, Aloul, Fadi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8702133/ https://www.ncbi.nlm.nih.gov/pubmed/34946438 http://dx.doi.org/10.3390/healthcare9121712

Ejemplares similares

Towards Validating the Effectiveness of Obstructive Sleep Apnea Classification from Electronic Health Records Using Machine Learning
por: Ramesh, Jayroop, et al.
Publicado: (2021)

A remote healthcare monitoring framework for diabetes prediction using machine learning
por: Ramesh, Jayroop, et al.
Publicado: (2021)

Atrial Fibrillation Classification with Smart Wearables Using Short-Term Heart Rate Variability and Deep Convolutional Neural Networks
por: Ramesh, Jayroop, et al.
Publicado: (2021)

Machine Learning Approaches to Predict Risks of Diabetic Complications and Poor Glycemic Control in Nonadherent Type 2 Diabetes
por: Fan, Yuting, et al.
Publicado: (2021)

Machine learning approaches for the prediction of postoperative complication risk in liver resection patients
por: Zeng, Siyu, et al.
Publicado: (2021)

A Fusion-Based Machine Learning Approach for the Prediction of the Onset of Diabetes
por: Nadeem, Muhammad Waqas, et al.
Publicado: (2021)

Survival Prediction in Diabetic Foot Ulcers: A Machine Learning Approach
por: Popa, Alina Delia, et al.
Publicado: (2023)

A survey on diabetes risk prediction using machine learning approaches
por: Firdous, Shimoo, et al.
Publicado: (2022)

Predicting new crescent moon visibility applying machine learning algorithms
por: Al-Rajab, Murad, et al.
Publicado: (2023)

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning
por: Lee, Sharen, et al.
Publicado: (2021)

Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review
por: Kee, Ooi Ting, et al.
Publicado: (2023)

A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images
por: Khandakar, Amith, et al.
Publicado: (2022)

A data-driven approach to predicting diabetes and cardiovascular disease with machine learning
por: Dinh, An, et al.
Publicado: (2019)

Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data
por: Ravaut, Mathieu, et al.
Publicado: (2021)

COVID-19 cases prediction by using hybrid machine learning and beetle antennae search approach
por: Zivkovic, Miodrag, et al.
Publicado: (2021)

Predicting Type 2 Diabetes Using Logistic Regression and Machine Learning Approaches
por: Joshi, Ram D., et al.
Publicado: (2021)

Predicting thromboembolic complications in COVID-19 ICU patients using machine learning
por: van de Sande, Davy, et al.
Publicado: (2020)

Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study
por: Schallmoser, Simon, et al.
Publicado: (2023)

Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis
por: Yamauchi, Takafumi, et al.
Publicado: (2021)

Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance
por: Alsariera, Yazan A., et al.
Publicado: (2022)

Factors Influencing the Utilization of Diabetes Complication Tests Under the COVID-19 Pandemic: Machine Learning Approach
por: Byeon, Haewon
Publicado: (2022)

Effects of Plasma Transfusion on Perioperative Bleeding Complications: A Machine Learning Approach
por: Ngufor, Che, et al.
Publicado: (2015)

A machine-learning approach to predict postprandial hypoglycemia
por: Seo, Wonju, et al.
Publicado: (2019)

A machine learning approach for the prediction of pulmonary hypertension
por: Leha, Andreas, et al.
Publicado: (2019)

Using Machine Learning to Predict Complications in Pregnancy: A Systematic Review
por: Bertini, Ayleen, et al.
Publicado: (2022)

Developing Machine Learning Algorithms to Predict Pulmonary Complications After Emergency Gastrointestinal Surgery
por: Xue, Qiong, et al.
Publicado: (2021)

Deep Personal Multitask Prediction of Diabetes Complication with Attentive Interactions Predicting Diabetes Complications by Multitask-Learning
por: Zuo, Ming, et al.
Publicado: (2022)

Validating machine learning approaches for prediction of donor related complication in microsurgical breast reconstruction: a retrospective cohort study
por: Myung, Yujin, et al.
Publicado: (2021)

Predicting Diabetes Mellitus With Machine Learning Techniques
por: Zou, Quan, et al.
Publicado: (2018)

Predicting the Onset of Diabetes with Machine Learning Methods
por: Chou, Chun-Yang, et al.
Publicado: (2023)

Development of a Machine Learning Algorithm for Prediction of Complications after Ankle Arthrodesis
por: Bugarin, Amador, et al.
Publicado: (2022)

Approaches for the Prediction of Leaf Wetness Duration with Machine Learning
por: Solís, Martín, et al.
Publicado: (2021)

An Ensemble Approach to Predict Early-Stage Diabetes Risk Using Machine Learning: An Empirical Study
por: Laila, Umm e, et al.
Publicado: (2022)

Multiple Machine Learning Approaches Based on Postoperative Prediction of Pulmonary Complications in Patients With Emergency Cerebral Hemorrhage Surgery
por: Jing, Xiaolei, et al.
Publicado: (2022)

Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery
por: Jiang, Haiye, et al.
Publicado: (2021)

A machine learning approach for predicting descending thoracic aortic diameter
por: Yu, Ronghuang, et al.
Publicado: (2023)

Machine learning approaches for the prediction of soil aggregate stability
por: Bouslihim, Yassine, et al.
Publicado: (2021)

Prediction of Breast Cancer using Machine Learning Approaches
por: Rabiei, Reza, et al.
Publicado: (2022)

Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches
por: Natu, Milind, et al.
Publicado: (2022)

A machine learning approach for early prediction of gestational diabetes mellitus using elemental contents in fingernails
por: Chan, Yun-Nam, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_fr208dhvevotll0i0a4m7stfj6