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However, appropriate assessment, management, and treatment have been shown to reduce the complications of GDM. This study introduces a machine learning-based stratification system for identifying patients at risk of exhibiting high blood glucose levels, based on daily blood glucose measurements and electronic health record (EHR) data from GDM patients. We internally trained and validated our model on a cohort of 1148 pregnancies at Oxford University Hospitals NHS Foundation Trust (OUH), and performed external validation on 709 patients from Royal Berkshire Hospital NHS Foundation Trust (RBH). We trained linear and non-linear tree-based regression models to predict the proportion of high-readings (readings above the UK\u2019s National Institute for Health and Care Excellence [NICE] guideline) a patient may exhibit in upcoming days, and found that XGBoost achieved the highest performance during internal validation (0.021 [CI 0.019\u20130.023], 0.482 [0.442\u20130.516], and 0.112 [0.109\u20130.116], for MSE, R2, MAE, respectively). The model also performed similarly during external validation, suggesting that our method is generalizable across different cohorts of GDM patients.<\/jats:p>","DOI":"10.3390\/s22134805","type":"journal-article","created":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T22:50:23Z","timestamp":1656283823000},"page":"4805","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Machine Learning-Based Risk Stratification for Gestational Diabetes Management"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0352-8452","authenticated-orcid":false,"given":"Jenny","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford OX3 7SQ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Clifton","sequence":"additional","affiliation":[{"name":"Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford OX3 7SQ, UK"},{"name":"Oxford-Suzhou Centre for Advanced Research, Suzhou 215000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0176-2651","authenticated-orcid":false,"given":"Jane E.","family":"Hirst","sequence":"additional","affiliation":[{"name":"Nuffield Department of Women\u2019s & Reproductive Health, University of Oxford, Oxford OX3 9DU, UK"},{"name":"The George Institute for Global Health, Imperial College London, London WB12 0BZ, UK"},{"name":"John Radcliffe Hosptial Women\u2019s Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7021-1191","authenticated-orcid":false,"given":"Foteini K.","family":"Kavvoura","sequence":"additional","affiliation":[{"name":"Centre for Diabetes & Endocrinology, Royal Berkshire Hospitals NHS Foundation Trust, Reading RG1 5BS, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George","family":"Farah","sequence":"additional","affiliation":[{"name":"Centre for Diabetes & Endocrinology, Royal Berkshire Hospitals NHS Foundation Trust, Reading RG1 5BS, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1927-1594","authenticated-orcid":false,"given":"Lucy","family":"Mackillop","sequence":"additional","affiliation":[{"name":"Nuffield Department of Women\u2019s & Reproductive Health, University of Oxford, Oxford OX3 9DU, UK"},{"name":"John Radcliffe Hosptial Women\u2019s Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK"},{"name":"Sensyne Health, Schr\u00f6dinger Building, Science Park, Oxford OX4 4GE, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6140-3394","authenticated-orcid":false,"given":"Huiqi","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford OX3 7SQ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,25]]},"reference":[{"key":"ref_1","unstructured":"(2022, April 21). IDF Atlas, The International Diabetes Federation Altas Tenth Edition 2021. Available online: https:\/\/idf.org\/aboutdiabetes\/what-is-diabetes\/facts-figures.html."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"American Diabetes Association (2003). Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care, 26, S5\u2013S20.","DOI":"10.2337\/diacare.26.2007.S5"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Oskovi-Kaplan, Z.A., and Ozgu-Erdinc, A.S. (2020). Management of gestational diabetes mellitus. Diabetes: From Research to Clinical Practice, Springer.","DOI":"10.1007\/5584_2020_552"},{"key":"ref_4","first-page":"CD012327","article-title":"Treatments for women with gestational diabetes mellitus: An overview of Cochrane systematic reviews","volume":"8","author":"Martis","year":"2018","journal-title":"Cochrane Database Syst. Rev."},{"key":"ref_5","first-page":"1767","article-title":"Management of gestational diabetes mellitus","volume":"68","author":"Turok","year":"2003","journal-title":"Am. Fam. Physician"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1177\/1932296814542271","article-title":"Development of a real-time smartphone solution for the management of women with or at high risk of gestational diabetes","volume":"8","author":"Mackillop","year":"2014","journal-title":"J. Diabetes Sci. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"National Institute for Health and Care Excellence (2022, January 15). Diabetes in Pregnancy: Management of Diabetes and Its Complications from Preconception to the Postnatal Period. NG3. 15 February 2015. Available online: https:\/\/www.nice.org.uk\/guidance\/ng3.","DOI":"10.15277\/bjdvd.2015.029"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"108044","DOI":"10.1016\/j.diabres.2020.108044","article-title":"Maternal age and the risk of gestational diabetes mellitus: A systematic review and meta-analysis of over 120 million participants","volume":"162","author":"Li","year":"2020","journal-title":"Diabetes Res. Clin. Pract."},{"key":"ref_9","first-page":"541","article-title":"Longitudinal changes in glucose during pregnancy in women with gestational diabetes risk factors","volume":"65","author":"Arenas","year":"2021","journal-title":"Diabetologia"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/s11892-018-1093-2","article-title":"Oral agents for the treatment of gestational diabetes","volume":"18","author":"Finneran","year":"2018","journal-title":"Curr. 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