Literature DB >> 32321867

The evidence landscape in precision medicine.

Spencer Phillips Hey1,2, Cory V Gerlach3,4,5, Garrett Dunlap3,6, Vinay Prasad7, Aaron S Kesselheim8,2.   

Abstract

Precision medicine is beginning to make an impact on the treatment of different diseases, but there are still challenges that must be overcome, such as the complexity of interventions, the need for marker validation, and the level of evidence necessary to demonstrate effectiveness. In this Perspective, we describe how evidence landscapes can help to address these challenges.
Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Mesh:

Year:  2020        PMID: 32321867     DOI: 10.1126/scitranslmed.aaw7745

Source DB:  PubMed          Journal:  Sci Transl Med        ISSN: 1946-6234            Impact factor:   17.956


  4 in total

1.  Multi-parametric characterization of drug effects on cells.

Authors:  Yael Paran; Yuvalal Liron; Sarit Batsir; Nicola Mabjeesh; Benjamin Geiger; Zvi Kam
Journal:  F1000Res       Date:  2020-10-05

2.  Popular deep learning algorithms for disease prediction: a review.

Authors:  Zengchen Yu; Ke Wang; Zhibo Wan; Shuxuan Xie; Zhihan Lv
Journal:  Cluster Comput       Date:  2022-09-13       Impact factor: 2.303

3.  Stakeholders Perceptions of Barriers to Precision Medicine Adoption in the United States.

Authors:  Monica M Schroll; Arushi Agarwal; Olivia Foroughi; Emily Kong; Omar Perez; Daryl Pritchard; Tom Breur; Kristen Garner Amanti; Gary Gustavsen
Journal:  J Pers Med       Date:  2022-06-22

Review 4.  Translational precision medicine: an industry perspective.

Authors:  Dominik Hartl; Valeria de Luca; Anna Kostikova; Jason Laramie; Scott Kennedy; Enrico Ferrero; Richard Siegel; Martin Fink; Sohail Ahmed; John Millholland; Alexander Schuhmacher; Markus Hinder; Luca Piali; Adrian Roth
Journal:  J Transl Med       Date:  2021-06-05       Impact factor: 5.531

  4 in total

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