Cystic fibrosis carriers are at increased risk for a wide range of cystic fibrosis-related conditions. Miller Aaron C et al. Proceedings of the National Academy of Sciences of the United States of America 2019 Dec

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Last Posted: Jan 03, 2020

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• Cystic fibrosis carriers are at increased risk for a wide range of cystic fibrosis-related conditions.
  Miller Aaron C et al. Proceedings of the National Academy of Sciences of the United States of America 2019 Dec
• A combined strategy of feature selection and machine learning to identify predictors of prediabetes.
  De Silva Kushan et al. Journal of the American Medical Informatics Association : JAMIA 2019 Dec
• Genetic Profiling of Breast Cancer with and Without Preexisting Metabolic Disease.
  Jing Wenjiang et al. Translational oncology 2019 Dec 13(2) 245-253
• Diabetes mellitus, glycemic traits, and cerebrovascular disease: a Mendelian randomization study
  MC Georgakis et al, MedRXIV, December 30, 2019
• Diabetes Goes Digital
  CDC, 2019
• A cross-sectional study of patients referred for HNF1B-MODY genetic testing due to cystic kidneys and diabetes.
  Sztromwasser Pawel et al. Pediatric diabetes 2019 Dec
• Implementation of machine learning algorithms to create diabetic patient re-admission profiles.
  Alloghani Mohamed et al. BMC medical informatics and decision making 2019 Dec 19(Suppl 9) 253
• Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.
  Abbas Hasan T et al. PloS one 2019 14(12) e0219636
• Use of smartphones for detecting diabetic retinopathy: a protocol for a scoping review of diagnostic test accuracy studies.
  Tan Choon Han et al. BMJ open 2019 Dec 9(12) e028811
• Using machine learning models to improve stroke risk level classification methods of China national stroke screening.
  Li Xuemeng et al. BMC medical informatics and decision making 2019 Dec 19(1) 261

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