Mining new applications from current algorithms

Chung Ho Hsieh; Usman Iqbal; Yu Chuan (Jack) Li

doi:10.1016/S0169-2607(17)31259-2

Mining new applications from current algorithms

Chung Ho Hsieh
, Usman Iqbal
, Yu Chuan (Jack) Li^*

^*Corresponding author for this work

Research output: Contribution to journal › Editorial › Research

Abstract

New technologies and the accessibility of big data have led to enormously increased number of new algorithms with 10-fold to 100-fold improvement in performance. This does not mean the traditional algorithms are out-of-date. This month’s Editor’s Choice articles demonstrates how to use the current algorithms in new ways.

Original language	English
Pages (from-to)	A1-A1
Number of pages	1
Journal	Computer Methods and Programs in Biomedicine
Volume	152
DOIs	https://doi.org/10.1016/S0169-2607(17)31259-2
Publication status	Published - Dec 2017
Externally published	Yes

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Cite this

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title = "Mining new applications from current algorithms",

abstract = "New technologies and the accessibility of big data have led to enormously increased number of new algorithms with 10-fold to 100-fold improvement in performance. This does not mean the traditional algorithms are out-of-date. This month{\textquoteright}s Editor{\textquoteright}s Choice articles demonstrates how to use the current algorithms in new ways.",

author = "Hsieh, \{Chung Ho\} and Usman Iqbal and \{(Jack) Li\}, \{Yu Chuan\}",

year = "2017",

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language = "English",

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AU - Hsieh, Chung Ho

AU - Iqbal, Usman

AU - (Jack) Li, Yu Chuan

PY - 2017/12

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N2 - New technologies and the accessibility of big data have led to enormously increased number of new algorithms with 10-fold to 100-fold improvement in performance. This does not mean the traditional algorithms are out-of-date. This month’s Editor’s Choice articles demonstrates how to use the current algorithms in new ways.

AB - New technologies and the accessibility of big data have led to enormously increased number of new algorithms with 10-fold to 100-fold improvement in performance. This does not mean the traditional algorithms are out-of-date. This month’s Editor’s Choice articles demonstrates how to use the current algorithms in new ways.

UR - https://www.scopus.com/pages/publications/85031815127

U2 - 10.1016/S0169-2607(17)31259-2

DO - 10.1016/S0169-2607(17)31259-2

M3 - Editorial

C2 - 29054265

AN - SCOPUS:85031815127

SN - 0169-2607

VL - 152

SP - A1-A1

JO - Computer Methods and Programs in Biomedicine

JF - Computer Methods and Programs in Biomedicine

ER -

Mining new applications from current algorithms

Abstract

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