EconPapers    
Economics at your fingertips  
 

Massive datasets and machine learning for computational biomedicine: trends and challenges

Anton Kocheturov (), Panos M. Pardalos () and Athanasia Karakitsiou ()
Additional contact information
Anton Kocheturov: University of Florida
Panos M. Pardalos: University of Florida
Athanasia Karakitsiou: Technological Educational Institute of Central Macedonia

Annals of Operations Research, 2019, vol. 276, issue 1, No 2, 5-34

Abstract: Abstract This survey paper attempts to cover a broad range of topics related to computational biomedicine. The field has been attracting great attention due to a number of benefits it can provide the society with. New technological and theoretical advances have made it possible to progress considerably. Traditionally, problems emerging in this field are challenging from many perspectives. In this paper, we considered the influence of big data on the field, problems associated with massive datasets in biomedicine and ways to address these problems. We analyzed the most commonly used machine learning and feature mining tools and several new trends and tendencies such as deep learning and biological networks for computational biomedicine.

Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-018-2891-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:276:y:2019:i:1:d:10.1007_s10479-018-2891-2

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-018-2891-2

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:annopr:v:276:y:2019:i:1:d:10.1007_s10479-018-2891-2