PMID- 30232632
OWN - NLM
STAT- MEDLINE
DCOM- 20181211
LR  - 20230918
IS  - 1573-689X (Electronic)
IS  - 0148-5598 (Linking)
VI  - 42
IP  - 11
DP  - 2018 Sep 19
TI  - Systematic Review of an Automated Multiclass Detection and Classification System 
      for Acute Leukaemia in Terms of Evaluation and Benchmarking, Open Challenges, 
      Issues and Methodological Aspects.
PG  - 204
LID - 10.1007/s10916-018-1064-9 [doi]
AB  - This study aims to systematically review prior research on the evaluation and 
      benchmarking of automated acute leukaemia classification tasks. The review 
      depends on three reliable search engines: ScienceDirect, Web of Science and IEEE 
      Xplore. A research taxonomy developed for the review considers a wide perspective 
      for automated detection and classification of acute leukaemia research and 
      reflects the usage trends in the evaluation criteria in this field. The developed 
      taxonomy consists of three main research directions in this domain. The taxonomy 
      involves two phases. The first phase includes all three research directions. The 
      second one demonstrates all the criteria used for evaluating acute leukaemia 
      classification. The final set of studies includes 83 investigations, most of 
      which focused on enhancing the accuracy and performance of detection and 
      classification through proposed methods or systems. Few efforts were made to 
      undertake the evaluation issues. According to the final set of articles, three 
      groups of articles represented the main research directions in this domain: 56 
      articles highlighted the proposed methods, 22 articles involved proposals for 
      system development and 5 papers centred on evaluation and comparison. The other 
      taxonomy side included 16 main and sub-evaluation and benchmarking criteria. This 
      review highlights three serious issues in the evaluation and benchmarking of 
      multiclass classification of acute leukaemia, namely, conflicting criteria, 
      evaluation criteria and criteria importance. It also determines the weakness of 
      benchmarking tools. To solve these issues, multicriteria decision-making (MCDM) 
      analysis techniques were proposed as effective recommended solutions in the 
      methodological aspect. This methodological aspect involves a proposed decision 
      support system based on MCDM for evaluation and benchmarking to select suitable 
      multiclass classification models for acute leukaemia. The said support system is 
      examined and has three sequential phases. Phase One presents the identification 
      procedure and process for establishing a decision matrix based on a crossover of 
      evaluation criteria and acute leukaemia multiclass classification models. Phase 
      Two describes the decision matrix development for the selection of acute 
      leukaemia classification models based on the integrated Best and worst method 
      (BWM) and VIKOR. Phase Three entails the validation of the proposed system.
FAU - Alsalem, M A
AU  - Alsalem MA
AD  - Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, 
      Perak, Malaysia.
FAU - Zaidan, A A
AU  - Zaidan AA
AD  - Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, 
      Perak, Malaysia. aws.alaa@gmail.com.
FAU - Zaidan, B B
AU  - Zaidan BB
AD  - Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, 
      Perak, Malaysia.
FAU - Hashim, M
AU  - Hashim M
AD  - Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, 
      Perak, Malaysia.
FAU - Albahri, O S
AU  - Albahri OS
AD  - Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, 
      Perak, Malaysia.
FAU - Albahri, A S
AU  - Albahri AS
AD  - Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, 
      Perak, Malaysia.
FAU - Hadi, Ali
AU  - Hadi A
AD  - Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, 
      Perak, Malaysia.
FAU - Mohammed, K I
AU  - Mohammed KI
AD  - Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, 
      Perak, Malaysia.
LA  - eng
PT  - Journal Article
PT  - Review
PT  - Systematic Review
DEP - 20180919
PL  - United States
TA  - J Med Syst
JT  - Journal of medical systems
JID - 7806056
SB  - IM
MH  - Acute Disease
MH  - *Automation
MH  - *Benchmarking
MH  - Humans
MH  - Leukemia/*diagnosis
MH  - Research
MH  - Search Engine
OTO - NOTNLM
OT  - Acute leukaemia
OT  - Benchmarking
OT  - Detection
OT  - Evaluation
OT  - Evaluation criteria
OT  - MCDM
OT  - Multiclass classification
EDAT- 2018/09/21 06:00
MHDA- 2018/12/12 06:00
CRDT- 2018/09/21 06:00
PHST- 2018/07/18 00:00 [received]
PHST- 2018/09/06 00:00 [accepted]
PHST- 2018/09/21 06:00 [entrez]
PHST- 2018/09/21 06:00 [pubmed]
PHST- 2018/12/12 06:00 [medline]
AID - 10.1007/s10916-018-1064-9 [pii]
AID - 10.1007/s10916-018-1064-9 [doi]
PST - epublish
SO  - J Med Syst. 2018 Sep 19;42(11):204. doi: 10.1007/s10916-018-1064-9.