, Brat DJ, Verhaak RG, Aldape KD, Yung WK, Salama SR, Cooper LA, Rheinbay E, Miller CR, Vitucci M, Morozova O, Robertson AG, Noushmehr H, Laird PW, Cherniack AD, Akbani R, Huse JT, Ciriello G, Poisson LM, Barnholtz-Sloan JS, Berger MS, Brennan C, Colen RR, Colman H, Flanders AE, Giannini C, Grifford M, Iavarone A, […]
Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in […]
Human islet research is providing new insights into human islet biology and diabetes, using islets isolated at multiple US centers from donors with varying characteristics. This creates challenges for understanding, interpreting, and integrating research findings from the many laboratories that use these islets. In what is, to our knowledge, the first standardized assessment of human […]
Kayton NS, Poffenberger G, Henske J, Dai C, Thompson C, Aramandla R, Shostak A, Nicholson W, Brissova M, Bush WS, Powers AC,. Human islet research is providing new insights into human islet biology and diabetes, using islets isolated at multiple US centers from donors with varying characteristics. This creates challenges for understanding, interpreting, and integrating […]
The clinical course of multiple sclerosis (MS) is highly variable, and research data collection is costly and time consuming. We evaluated natural language processing techniques applied to electronic medical records (EMR) to identify MS patients and the key clinical traits of their disease course.We used four algorithms based on ICD-9 codes, text keywords, and medications […]
Davis MF, Sriram S, Bush WS, Denny JC, Haines JL,. The clinical course of multiple sclerosis (MS) is highly variable, and research data collection is costly and time consuming. We evaluated natural language processing techniques applied to electronic medical records (EMR) to identify MS patients and the key clinical traits of their disease course.We used […]