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Title:           Characterizing the clinical profile and prevalence of people with diabetes attended in the hospital setting by using unstructured healthcare data and natural language processing: the Diabetic@ study
Subject:         Diabetes Research and Clinical Practice, 226 (2025) 112214. doi:10.1016/j.diabres.2025.112214
Keywords:        Diabetes Mellitus (DM),Natural Language Processing (NLP),Machine Learning (ML),Unstructured Data,Diabetes Comorbidities,Diabetes Complications
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      Title: Characterizing the clinical profile and prevalence of people with diabetes attended in the hospital setting by using unstru ...
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        Title: 1 Introduction
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        Title: 2 Research design and methods
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          Title: 2.1 Study design and data source
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          Title: 2.2 Study population
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          Title: 2.3 Data extraction
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          Title: 2.4 Study variables
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          Title: 2.5 Classification of persons with DM: Classification predictive model training, validation and data analyses
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          Title: 2.6 Ethical considerations and study approval
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        Title: 3 Results
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          Title: 3.1 Study population
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          Title: 3.2 Prevalence of T1DM and T2DM in the hospital setting
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          Title: 3.3 Demographic and clinical characteristics of persons with DM in the hospital setting
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          Title: 3.4 Evolution of DM individuals in the hospital setting
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        Title: Appendix A Supplementary material
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   Type: CRC32
  Checksum: 1a6c72c3a4bc24046c9fecb68d207f02
   Type: MD5
  Checksum: 5e3e964329912aa698d11dd5cbea936b64f7b493
   Type: SHA-1
  Checksum: e4d9c106637d59a90ed35128a30928e61abf758e5608f57f1e96630e72a7ae58
   Type: SHA-256