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Special issue introduction: Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic

Special issue introduction: Statistical Methods in Precision Medicine: Diagnostic, Prognostic,... BIOSTATISTICS & EPIDEMIOLOGY 2021, VOL. 5, NO. 2, 93–99 https://doi.org/10.1080/24709360.2021.1953942 EDITORIAL Special issue introduction: Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic Dear Readers, We are delighted to oer ff this special issue of Biostatistics & Epidemiology on ‘Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic.’ Preci- sion medicine, often referred to as personalized medicine, has a relatively short history but presents great opportunities and challenges. As former US Health and Human Services Secre- tary Michael Leavitt said in a 2007 meeting of the Personalized Medicine Coalition, advances in science and technology present an unprecedented ‘opportunity to bring health care to a new levelofeeff ctivenessandsafety’[ 1]. In particular, recent advances have been made in omics- based in vitro measurements [2–4], quantitative imaging biomarkers [5], artificial intelligence/ machine learning [6], andelectronichealthrecordkeeping [7]. These advances and others have led to a surge in medical research activity into personalized medicine, which has been described as ‘providing the right drug for the right patient at the right time’ [8].Asaresult, the potential has never been greater to obtain powerful information for individualizing medical decision making, including but not limited to information on diagnosis, prognosis, and treat- ment selection, and for http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biostatistics & Epidemiology Taylor & Francis

Special issue introduction: Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic

Biostatistics & Epidemiology , Volume 5 (2): 7 – Jul 3, 2021

Special issue introduction: Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic

Abstract

BIOSTATISTICS & EPIDEMIOLOGY 2021, VOL. 5, NO. 2, 93–99 https://doi.org/10.1080/24709360.2021.1953942 EDITORIAL Special issue introduction: Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic Dear Readers, We are delighted to oer ff this special issue of Biostatistics & Epidemiology on ‘Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic.’ Preci- sion medicine, often referred to as...
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Publisher
Taylor & Francis
Copyright
This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
ISSN
2470-9379
eISSN
2470-9360
DOI
10.1080/24709360.2021.1953942
Publisher site
See Article on Publisher Site

Abstract

BIOSTATISTICS & EPIDEMIOLOGY 2021, VOL. 5, NO. 2, 93–99 https://doi.org/10.1080/24709360.2021.1953942 EDITORIAL Special issue introduction: Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic Dear Readers, We are delighted to oer ff this special issue of Biostatistics & Epidemiology on ‘Statistical Methods in Precision Medicine: Diagnostic, Prognostic, Predictive and Therapeutic.’ Preci- sion medicine, often referred to as personalized medicine, has a relatively short history but presents great opportunities and challenges. As former US Health and Human Services Secre- tary Michael Leavitt said in a 2007 meeting of the Personalized Medicine Coalition, advances in science and technology present an unprecedented ‘opportunity to bring health care to a new levelofeeff ctivenessandsafety’[ 1]. In particular, recent advances have been made in omics- based in vitro measurements [2–4], quantitative imaging biomarkers [5], artificial intelligence/ machine learning [6], andelectronichealthrecordkeeping [7]. These advances and others have led to a surge in medical research activity into personalized medicine, which has been described as ‘providing the right drug for the right patient at the right time’ [8].Asaresult, the potential has never been greater to obtain powerful information for individualizing medical decision making, including but not limited to information on diagnosis, prognosis, and treat- ment selection, and for

Journal

Biostatistics & EpidemiologyTaylor & Francis

Published: Jul 3, 2021

References