Early detection of type 2 diabetes mellitus using machine learning-based prediction models
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Early detection of type 2 diabetes mellitus using machine learning-based prediction models
Authors
Keywords
-
Journal
Scientific Reports
Volume 10, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-07-20
DOI
10.1038/s41598-020-68771-z
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Triglycerides: Emerging Targets in Diabetes Care? Review of Moderate Hypertriglyceridemia in Diabetes
- (2019) Anastasia-Stefania Alexopoulos et al. Current Diabetes Reports
- Development and validation of a predictive model for incident type 2 diabetes in middle-aged Mexican adults: the metabolic syndrome cohort
- (2019) Olimpia Arellano-Campos et al. BMC Endocrine Disorders
- A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
- (2019) Evangelia Christodoulou et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- A Prediction Model for Uncontrolled Type 2 Diabetes Mellitus Incorporating Area-level Social Determinants of Health
- (2019) Sanjay Basu et al. MEDICAL CARE
- Development of a screening tool using electronic health records for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose detection in the Slovenian population
- (2018) G. Štiglic et al. DIABETIC MEDICINE
- Predicting Diabetes Mellitus With Machine Learning Techniques
- (2018) Quan Zou et al. Frontiers in Genetics
- Prediction of lung cancer patient survival via supervised machine learning classification techniques
- (2017) Chip M. Lynch et al. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
- Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study
- (2017) André Rodrigues Olivera et al. Sao Paulo Medical Journal
- Machine Learning and Data Mining Methods in Diabetes Research
- (2017) Ioannis Kavakiotis et al. Computational and Structural Biotechnology Journal
- Validation of the Finnish Diabetes Risk Score (FINDRISC) questionnaire for undiagnosed type 2 diabetes screening in the Slovenian working population
- (2016) Gregor Štiglic et al. DIABETES RESEARCH AND CLINICAL PRACTICE
- Why screen for type 2 diabetes?
- (2016) David Cavan DIABETES RESEARCH AND CLINICAL PRACTICE
- Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View
- (2016) Wei Luo et al. JOURNAL OF MEDICAL INTERNET RESEARCH
- Facilitating the ethical use of health data for the benefit of society: electronic health records, consent and the duty of easy rescue
- (2016) Sebastian Porsdam Mann et al. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
- Prediction models for cardiovascular disease risk in the general population: systematic review
- (2016) Johanna A A G Damen et al. BMJ-British Medical Journal
- Comparison of Four Machine Learning Methods for Generating the GLASS Fractional Vegetation Cover Product from MODIS Data
- (2016) Linqing Yang et al. Remote Sensing
- Machine learning models in breast cancer survival prediction
- (2016) Mitra Montazeri et al. TECHNOLOGY AND HEALTH CARE
- Prediction models for cardiovascular disease risk in the general population: systematic review
- (2016) Johanna A A G Damen et al. BMJ-British Medical Journal
- Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records
- (2016) Riccardo Miotto et al. Scientific Reports
- Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico
- (2016) Michael A. Johansson et al. Scientific Reports
- Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement
- (2015) Gary S. Collins et al. ANNALS OF INTERNAL MEDICINE
- Evaluation of the Finnish Diabetes Risk Score (FINDRISC) for diabetes screening in occupational health care
- (2015) Godelieve Vandersmissen et al. International Journal of Occupational Medicine and Environmental Health
- Mobile Applications for Type 2 Diabetes Risk Estimation: a Systematic Review
- (2015) Nino Fijacko et al. JOURNAL OF MEDICAL SYSTEMS
- Machine learning applications in cancer prognosis and prediction
- (2015) Konstantina Kourou et al. Computational and Structural Biotechnology Journal
- Interaction between Glucose and Lipid Metabolism: More than Diabetic Dyslipidemia
- (2015) Klaus G. Parhofer Diabetes & Metabolism Journal
- Regularization Paths for Generalized Linear Models via Coordinate Descent
- (2015) Jerome Friedman et al. Journal of Statistical Software
- mice: Multivariate Imputation by Chained Equations inR
- (2015) Stef van Buuren et al. Journal of Statistical Software
- Using methods from the data-mining and machine-learning literature for disease classification and prediction: a case study examining classification of heart failure subtypes
- (2013) Peter C. Austin et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started