Connolly, B; Cohen, KB; Santel, D; Bayram, U; Pestian, J. A nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support. BMC Bioinformatics. 2017; 18(1):361-361.
This study develops a method that allows for a more robust way to determine the value of reesults dereived from machine learning models for clinical care, so that clinical researchers can better assess the usefulness of employing these models for predictive decision-making.
Lingren, T; Sadhasivam, S; Zhang, X; Marsolo, K. Electronic medical records as a replacement for prospective research data collection in postoperative pain and opioid response studies. International Journal of Medical Informatics. 2018; 111:45-50.
This study determined that using the electronic medical record as a mechanism for capturing prospective data for pain and opioid research can be a more efficient and equally accurate method than using traditional clinical research data capture approaches.
Liu, X; Yagi, H; Saeed, S; Bais, AS; Gabriel, GC; Chen, Z; Peterson, KA; Li, Y; Schwartz, MC; Reynolds, WT; Saydmohammed, M; Gibbs, B; Wu, Y; Devine, W; Chatterjee, B; Klena, NT; Kostka, D; de Mesy Bentley, KL; Ganapathiraju, MK; Dexheimer, P; Leatherbury, L; Khalifa, O; Bhagat, A; Zahid, M; Pu, W; Watkins, S; Grossfeld, P; Murray, SA; Porter, GA, Jr; Tsang, M; Martin, LJ; Benson, DW; Aronow, BJ; Lo, CW. The complex genetics of hypoplastic left heart syndrome. Nature Genetics. 2017; 49(7):1152-1159.
This study used genetics, functional genomics, and gene editing techniques to identify a number of known and new genes and gene combinations that contribute to the congenital cardiac defect hypoplastic left heart syndrome.
Ni, Y; Lingren, T; Hall, ES; Leonard, M; Melton, K; Kirkendall, ES Designing and evaluating an automated system for real-time medication administration error detection in a neonatal intensive care unit Journal of the American Medical Informatics Association. 2018; 25(5):555-563.
This study designed a highly effective, automated system for identifying medication administration errors in neonatal intensive care units that has promise for reducing such errors for newborns.
Zhu, X; Shah, A; Swertfeger, D; Li, H; Ren, S; Melchior, J; Gordon, S; Davidson, W; Lu, L. High-Density Lipoproteins-Associated Proteins and Subspecies Related to Arterial Stiffness in Young Adults with Type 2 Diabetes Mellitus. Complexity. 2018; 2018:1-14.
This study looked at high-density lipoproteins in patients with Type 2 diabetes and found subsets of proteins that may either be protective of or contributing to symptoms of arterial stiffness.