Institution
University of Colorado Denver
Education•Denver, Colorado, United States•
About: University of Colorado Denver is a education organization based out in Denver, Colorado, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 27444 authors who have published 57213 publications receiving 2539937 citations. The organization is also known as: CU Denver & UCD.
Topics: Population, Poison control, Health care, Diabetes mellitus, Cancer
Papers published on a yearly basis
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TL;DR: Vision gains during the first 2 years were not maintained, but 50% of eyes had VA of 20/40 or better, confirming anti-vascular endothelial growth factor therapy as a major long-term therapeutic advance for neovascular AMD.
503 citations
TL;DR: It is shown that fructose also stimulates triglyceride synthesis via a purine-degrading pathway that is triggered from the rapid phosphorylation of fructose by fructokinase, which provides new insights into the pathogenesis of hepatic fat accumulation under normal and diseased states.
503 citations
TL;DR: A 25-year program of research that has attempted to improve the early health and development of low-income mothers and children and their future life trajectories with prenatal and infancy home visiting by nurses is summarized.
Abstract: This paper summarizes a 25-year program of research that has attempted to improve the early health and development of low-income mothers and children and their future life trajectories with prenatal and infancy home visiting by nurses The program has been tested in two separate large-scale randomized controlled trials with different populations living in different contexts The program has been successful in improving parental care of the child as reflected in fewer injuries and ingestions that may be associated with child abuse and neglect; and maternal life-course, reflected in fewer subsequent pregnancies, greater work force participation, and reduced use of public assistance and food stamps In the first trial, the program also produced long-term effects on the number of arrests, convictions, emergent substance use, and promiscuous sexual activity of 15-year-old children whose nurse-visited mothers were low-income and unmarried when they registered in the study during pregnancy Since 1996, the program has been offered for public investment outside of research contexts Careful attention has been given to ensuring that the program is replicated with fidelity to the model tested in the scientifically controlled studies by working with community leaders to ensure that organization and community contexts are favorable for the program; by providing the nurses with excellent training and technical assistance and detailed visit-by-visit guidelines; and by providing organizations with a web-based clinical information system that creates a basis for monitoring program performance and continuous quality improvement
503 citations
Children's Oncology Group1, University of New Mexico2, St. Jude Children's Research Hospital3, University of Alabama at Birmingham4, University of Georgia5, New York University6, University of Florida7, Medical College of Wisconsin8, Children's National Medical Center9, University of Colorado Denver10
TL;DR: Observations suggest that activation of CRLF2 expression, mutation of JAK kinases, and alterations of IKZF1 cooperate to promote B-cell leukemogenesis and identify these pathways as important therapeutic targets in this disease.
502 citations
TL;DR: Examples of current applications of machine learning and artificial intelligence techniques in diagnostic radiology and the future impact and natural extension of these techniques in radiology practice are discussed.
Abstract: Recent advances and future perspectives of machine learning techniques offer promising applications in medical imaging. Machine learning has the potential to improve different steps of the radiology workflow including order scheduling and triage, clinical decision support systems, detection and interpretation of findings, postprocessing and dose estimation, examination quality control, and radiology reporting. In this article, the authors review examples of current applications of machine learning and artificial intelligence techniques in diagnostic radiology. In addition, the future impact and natural extension of these techniques in radiology practice are discussed.
© RSNA, 2018
501 citations
Authors
Showing all 27683 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Matthew Meyerson | 194 | 553 | 243726 |
| Charles A. Dinarello | 190 | 1058 | 139668 |
| Gad Getz | 189 | 520 | 247560 |
| Gordon B. Mills | 187 | 1273 | 186451 |
| Jasvinder A. Singh | 176 | 2382 | 223370 |
| David Haussler | 172 | 488 | 224960 |
| Donald G. Truhlar | 165 | 1518 | 157965 |
| Charles M. Perou | 156 | 573 | 202951 |
| David Cella | 156 | 1258 | 106402 |
| Bruce D. Walker | 155 | 779 | 86020 |
| Marco A. Marra | 153 | 620 | 184684 |
| Thomas E. Starzl | 150 | 1625 | 91704 |
| Marc Humbert | 149 | 1184 | 100577 |
| Rajesh Kumar | 149 | 4439 | 140830 |
| Martin J. Blaser | 147 | 820 | 104104 |