GlyCU-related Publications and Patents
Pappada SM, Woodling K, Owais MH, Zink EM, Dahbour L, Tripathi RS, Khuder SA, Papadimos TJ, Continuous glucose monitoring identifies relationship between optimized glycemic control and post-discharge acute care facility needs, BMC Res Notes, 2018, 11:533.
Pappada SM, Cameron BD, Tulman DB, Bourey RE, Borst MJ, et al., Evaluation of a Model for Glycemic Prediction in Critically Ill Surgical Patients. PLoS ONE, 2013, 8(7).
Pappada SM, Cameron BD, Rosman PM, Papadimos TJ, Borst MJ, Bourey RE. Neural Network Based Real-time Prediction of Glucose in Patients with Insulin Dependent Diabetes, Diabetes Technology and Therapeutics, February 2011, 13(2), pp. 135-141.
Papadimos TJ, Pappada SM, Lather JD, Bazalitski V, Stawicki SP, Cameron BD, Pan ZK, Correlation between CCL20 and serum glucose in postoperative coronary bypass patient: A call for further investigation. OPUS 12 Scientist 2010; 4(1):1-2.
Pappada SM, Borst MJ, Cameron BD, Bourey RJ, Lather JD, Shipp DM, Chiricolo A, Papadimos TJ, Development of a neural network model for predicting glucose levels in a surgical critical care setting, Patient Safety in Surgery 2010, 4:15.
Pappada SM, Cameron BD, Rosman PM. Development of a Neural Network for Prediction Glucose Concentration in Type I Diabetes Patients. Journal of Diabetes Science and Technology, Sept. 2008, Vol 2. Issue 5, p.792-801.
Cameron BD and Pappada SM Multifunctional neural network system and use thereof for glycemic forecasting U.S. Patent No. 8,762,306 B2
Cameron BD and Pappada SM Neural Network System and Uses Thereof U.S. Patent No. 9,076,107 B2
For more information about GlyCU publications and patents, please contact Jeffrey Morrill at firstname.lastname@example.org.