D
David K. Williams
Researcher at University of Arkansas for Medical Sciences
Publications - 36
Citations - 3923
David K. Williams is an academic researcher from University of Arkansas for Medical Sciences. The author has contributed to research in topics: Telemedicine & Collaborative Care. The author has an hindex of 14, co-authored 33 publications receiving 3139 citations.
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Journal ArticleDOI
Purposeful selection of variables in logistic regression
TL;DR: An algorithm which automates the purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process and has the capability of retaining important confounding variables, resulting potentially in a slightly richer model.
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A randomized trial of telemedicine-based collaborative care for depression
John C. Fortney,Jeffrey M. Pyne,Mark J. Edlund,David K. Williams,Dean E. Robinson,Dean E. Robinson,Dinesh Mittal,Kathy L. Henderson +7 more
TL;DR: Collaborative care can be successfully adapted for primary care clinics without on-site psychiatrists using telemedicine technologies.
Journal ArticleDOI
Practice-Based Versus Telemedicine-Based Collaborative Care for Depression in Rural Federally Qualified Health Centers: A Pragmatic Randomized Comparative Effectiveness Trial
John C. Fortney,Jeffrey M. Pyne,Sip B. Mouden,Dinesh Mittal,Teresa J. Hudson,Gary W. Schroeder,David K. Williams,Carol A. Bynum,Rhonda Mattox,Kathryn Rost +9 more
TL;DR: Contracting with an off-site telemedicine-based collaborative care team can yield better outcomes than implementing practice- based collaborative care with locally available staff, according to this multisite randomized pragmatic comparative effectiveness trial.
Theoretical Biology and Medical Modelling
TL;DR: The proposed hypertabastic model shows to be a flexible and promising alternative to practitioners in this field and demonstrates an accelerated failure time version of the model by applying it to data from a randomized study of glioma patients who underwent radiotherapy treatment with and without radiosensitizer misonidazole.
Journal ArticleDOI
Hyperbolastic growth models: theory and application
TL;DR: A new family of growth models called hyperbolastic models are developed that predict the volumetric growth behavior of multicellular tumor spheroids with a high degree of accuracy and can be a valuable predictive tool in many areas of biomedical and epidemiological research.