Machine learning models to predict onset of dementia: A label learning approach

Alzheimer's and Dementia: Translational Research and Clinical Interventions - Tập 5 - Trang 918-925 - 2019
Vijay S. Nori1, Christopher A. Hane1, William H. Crown1, Rhoda Au2, William J. Burke3, Darshak M. Sanghavi1, Paul Bleicher1
1OptumLabs, Optum, Cambridge, MA, USA
2Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
3Psychiatry, Banner Alzheimer's Institute, Phoenix, AZ, USA

Tóm tắt

AbstractIntroductionThe study objective was to build a machine learning model to predict incident mild cognitive impairment, Alzheimer's Disease, and related dementias from structured data using administrative and electronic health record sources.MethodsA cohort of patients (n = 121,907) and controls (n = 5,307,045) was created for modeling using data within 2 years of patient's incident diagnosis date. Additional cohorts 3–8 years removed from index data are used for prediction. Training cohorts were matched on age, gender, index year, and utilization, and fit with a gradient boosting machine, lightGBM.ResultsIncident 2‐year model quality on a held‐out test set had a sensitivity of 47% and area‐under‐the‐curve of 87%. In the 3‐year model, the learned labels achieved 24% (71%), which dropped to 15% (72%) in year 8.DiscussionThe ability of the model to discriminate incident cases of dementia implies that it can be a worthwhile tool to screen patients for trial recruitment and patient management.

Tài liệu tham khảo

M.J.Prince.World Alzheimer Report 2011: the benefits of early diagnosis and intervention 2011.https://www.alz.co.uk/research/world‐report‐2011Accessed June 25 2019. 10.1016/j.jalz.2013.11.006 Byeon H., 2015, A prediction model for mild cognitive impairment using random forests, Int J Adv Comput Sci App, 6, 8 10.1212/WNL.0b013e3181a81636 10.1016/S2213-8587(13)70048-2 10.1016/j.jalz.2013.05.1772 10.1016/S1474-4422(06)70537-3 10.1001/archneurol.2010.136 Albrecht J.S., 2018, Predicting diagnosis of Alzheimer's disease and related dementias using administrative claims, JMCP, 24, 1138, 10.18553/jmcp.2018.24.11.1138 10.1371/journal.pone.0203246 10.1377/hlthaff.2014.0038 10.1186/1748-5908-9-31 10.2200/S00196ED1V01Y200906AIM006 CMS ICD10 GEMS.https://www.cms.gov/Medicare/Coding/ICD10/2018‐ICD‐10‐CM‐and‐GEMs.htmlAccessed June 25 2019. Ke G., 2017, Advances in Neural Information Processing Systems 30, 3146 10.1371/journal.pone.0136181 So A., 2017, Early diagnosis of dementia from clinical data by machine learning techniques, Appl Sci, 7, 651, 10.3390/app7070651 10.1038/s41598-017-06624-y Shankle W.R., 1997, Lecture Notes in Artificial Intelligence: Artificial Intelligence in Medicine, 71 10.1111/jon.12214 10.1093/brain/awm319 10.1016/j.neuroimage.2003.09.027 10.3174/ajnr.A0620 10.7326/0003-4819-122-6-199503150-00004 10.1111/j.1532-5415.2004.52301.x 10.1111/j.1532-5415.1999.tb04580.x 10.3233/JAD-131622 10.1002/ejhf.631 10.3233/JAD-132363 10.1038/ncpneuro0124 10.1001/jamainternmed.2019.0677
Thông tin
Thông tin xuất bản

Alzheimer's and Dementia: Translational Research and Clinical Interventions

Tập 5

918-925

Thông tin tác giả