2015
DOI: 10.1089/big.2015.0020
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Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors

Abstract: We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative claims, pharmacy records, healthcare utilization, and laboratory results of 4.1 million individuals between 2005 and 2009, an initial set of 42,000 variables … Show more

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Cited by 179 publications
(137 citation statements)
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References 52 publications
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“…The second category deals with disease prediction and diagnosis [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76]. Numerous algorithms and different approaches have been applied, such as traditional machine learning algorithms, ensemble learning approaches and association rule learning in order to achieve the best classification accuracy.…”
Section: Dm Through Machine Learning and Data Miningmentioning
confidence: 99%
See 1 more Smart Citation
“…The second category deals with disease prediction and diagnosis [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76]. Numerous algorithms and different approaches have been applied, such as traditional machine learning algorithms, ensemble learning approaches and association rule learning in order to achieve the best classification accuracy.…”
Section: Dm Through Machine Learning and Data Miningmentioning
confidence: 99%
“…With respect to high dimensional datasets, Razavian et al [44] used a dataset containing 4.1 million individuals and 42K variables from administrative claims, pharmacy records, healthcare utilization, and laboratory results between 2005 and 2009, to build predictive models (based on logistic regression) for different onsets of T2D prediction.…”
Section: Dm Through Machine Learning and Data Miningmentioning
confidence: 99%
“…For noisy OR, all the parameters were learned jointly. L1 regularization was used for logistic regression both to prevent overfitting and to encourage sparsity, which was desirable as we expect most diseases to cause only a small number of symptoms 35 . Laplacian smoothing was used to prevent overfitting for naive Bayes.…”
Section: Methodsmentioning
confidence: 99%
“…Данные некоторых исследований указывают, что гиперинсулинемия коррелирует с другими факто-рами риска, такими как повышенный индекс массы тела (ИМТ), ожирение абдоминального типа, АГ, увеличение содержания триглицеридов, развитие сердечно-сосудистых заболеваний [28].…”
Section: ев аль-травнехunclassified