Literature DB >> 30965188

Big data analytics for personalized medicine.

Davide Cirillo1, Alfonso Valencia2.   

Abstract

Big Data are radically changing biomedical research. The unprecedented advances in automated collection of large-scale molecular and clinical data pose major challenges to data analysis and interpretation, calling for the development of new computational approaches. The creation of powerful systems for the effective use of biomedical Big Data in Personalized Medicine (a.k.a. Precision Medicine) will require significant scientific and technical developments, including infrastructure, engineering, project and financial management. We review here how the evolution of data-driven methods offers the possibility to address many of these problems, guiding the formulation of hypotheses on systems functioning and the generation of mechanistic models, and facilitating the design of clinical procedures in Personalized Medicine.
Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Year:  2019        PMID: 30965188     DOI: 10.1016/j.copbio.2019.03.004

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  20 in total

Review 1.  Mitigating the adverse health effects and costs associated with smoking after a cancer diagnosis.

Authors:  Graham W Warren
Journal:  Transl Lung Cancer Res       Date:  2019-05

Review 2.  The application of big data to cardiovascular disease: paths to precision medicine.

Authors:  Jane A Leopold; Bradley A Maron; Joseph Loscalzo
Journal:  J Clin Invest       Date:  2020-01-02       Impact factor: 14.808

Review 3.  Fabrication approaches for high-throughput and biomimetic disease modeling.

Authors:  Mackenzie L Grubb; Steven R Caliari
Journal:  Acta Biomater       Date:  2021-03-11       Impact factor: 10.633

Review 4.  Targeted Perfusion Therapy in Spinal Cord Trauma.

Authors:  Samira Saadoun; Marios C Papadopoulos
Journal:  Neurotherapeutics       Date:  2020-04       Impact factor: 7.620

5.  A multi-source data integration approach reveals novel associations between metabolites and renal outcomes in the German Chronic Kidney Disease study.

Authors:  Michael Altenbuchinger; Helena U Zacharias; Stefan Solbrig; Andreas Schäfer; Mustafa Büyüközkan; Ulla T Schultheiß; Fruzsina Kotsis; Anna Köttgen; Rainer Spang; Peter J Oefner; Jan Krumsiek; Wolfram Gronwald
Journal:  Sci Rep       Date:  2019-09-27       Impact factor: 4.379

Review 6.  Nursing Personnel in the Era of Personalized Healthcare in Clinical Practice.

Authors:  Marios Spanakis; Athina E Patelarou; Evridiki Patelarou
Journal:  J Pers Med       Date:  2020-06-29

Review 7.  A Systematic Review of Machine Learning Techniques in Hematopoietic Stem Cell Transplantation (HSCT).

Authors:  Vibhuti Gupta; Thomas M Braun; Mosharaf Chowdhury; Muneesh Tewari; Sung Won Choi
Journal:  Sensors (Basel)       Date:  2020-10-27       Impact factor: 3.576

Review 8.  Machine Learning Methods in Drug Discovery.

Authors:  Lauv Patel; Tripti Shukla; Xiuzhen Huang; David W Ussery; Shanzhi Wang
Journal:  Molecules       Date:  2020-11-12       Impact factor: 4.411

9.  Automatic Quantification of Cardiomyocyte Dimensions and Connexin 43 Lateralization in Fluorescence Images.

Authors:  Antoni Oliver-Gelabert; Laura García-Mendívil; José María Vallejo-Gil; Pedro Carlos Fresneda-Roldán; Katarína Andelová; Javier Fañanás-Mastral; Manuel Vázquez-Sancho; Marta Matamala-Adell; Fernando Sorribas-Berjón; Carlos Ballester-Cuenca; Narcisa Tribulova; Laura Ordovás; Emiliano Raúl Diez; Esther Pueyo
Journal:  Biomolecules       Date:  2020-09-17

10.  Personalized prescription of ACEI/ARBs for hypertensive COVID-19 patients.

Authors:  Agni Orfanoudaki; Holly Wiberg; Dimitris Bertsimas; Alison Borenstein; Luca Mingardi; Omid Nohadani; Bartolomeo Stellato; Pankaj Sarin; Dirk J Varelmann; Vicente Estrada; Carlos Macaya; Iván J Núñez Gil
Journal:  Health Care Manag Sci       Date:  2021-03-15
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