PMID- 36673624
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230201
IS  - 2227-9032 (Print)
IS  - 2227-9032 (Electronic)
IS  - 2227-9032 (Linking)
VI  - 11
IP  - 2
DP  - 2023 Jan 13
TI  - Selection of an Efficient Classification Algorithm for Ambient Assisted Living: 
      Supportive Care for Elderly People.
LID - 10.3390/healthcare11020256 [doi]
LID - 256
AB  - Ambient Assisted Living (AAL) is a medical surveillance system comprised of 
      connected devices, healthcare sensor systems, wireless communications, computer 
      hardware, and software implementations. AAL could be used for an extensive 
      variety of purposes, comprising preventing, healing, as well as improving the 
      health and wellness of elderly individuals. AAL intends to ensure the wellbeing 
      of elderly persons while also spanning the number of years seniors can remain 
      independent in their preferred surroundings. It also decreases the quantity of 
      family caregivers by giving patients control over their health situations. To 
      avert huge costs as well as possible adverse effects on standard of living, 
      classifiers must be used to distinguish between adopters as well as nonadopters 
      of such innovations. With the development of numerous classification algorithms, 
      selecting the best classifier became a vital and challenging step in technology 
      acceptance. Decision makers must consider several criteria from different domains 
      when selecting the best classifier. Furthermore, it is critical to define the 
      best multicriteria decision-making strategy for modelling technology acceptance. 
      Considering the foregoing, this research reports the incorporation of the 
      multicriteria decision-making (MCDM) method which is founded on the fuzzy method 
      for order of preference by similarity to ideal solution (TOPSIS) to identify the 
      top classifier for continuing toward supporting AAL implementation research. The 
      results indicate that the classification algorithm KNN is the preferred technique 
      among the collection of different classification algorithms for the ambient 
      assisted living system.
FAU - Alluhaibi, Reyadh
AU  - Alluhaibi R
AUID- ORCID: 0000-0001-5794-1002
AD  - Department of Computer Science, College of Computer Science and Engineering, 
      Taibah University, Madinah 41477, Saudi Arabia.
FAU - Alharbe, Nawaf
AU  - Alharbe N
AUID- ORCID: 0000-0002-1900-420X
AD  - Department of Computer Science, Applied College, Taibah University, Madinah 
      46537, Saudi Arabia.
FAU - Aljohani, Abeer
AU  - Aljohani A
AD  - Department of Computer Science, Applied College, Taibah University, Madinah 
      46537, Saudi Arabia.
FAU - Al Mamlook, Rabia Emhmed
AU  - Al Mamlook RE
AUID- ORCID: 0000-0002-2523-7819
AD  - Department of Industrial Engineering and Engineering Management, Western Michigan 
      University, Kalamazoo, MI 49008, USA.
AD  - Department of Aeronautical Engineering, Al Zawiya University (Seventh of April 
      University), Al Zawiya City P.O. Box 16418, Libya.
LA  - eng
PT  - Journal Article
DEP - 20230113
PL  - Switzerland
TA  - Healthcare (Basel)
JT  - Healthcare (Basel, Switzerland)
JID - 101666525
PMC - PMC9859445
OTO - NOTNLM
OT  - AAL
OT  - MCDM
OT  - elderly people
OT  - fuzzy TOPSIS
OT  - supportive care
COIS- The authors declare no conflict of interest.
EDAT- 2023/01/22 06:00
MHDA- 2023/01/22 06:01
PMCR- 2023/01/13
CRDT- 2023/01/21 01:19
PHST- 2022/09/20 00:00 [received]
PHST- 2022/11/03 00:00 [revised]
PHST- 2022/11/23 00:00 [accepted]
PHST- 2023/01/21 01:19 [entrez]
PHST- 2023/01/22 06:00 [pubmed]
PHST- 2023/01/22 06:01 [medline]
PHST- 2023/01/13 00:00 [pmc-release]
AID - healthcare11020256 [pii]
AID - healthcare-11-00256 [pii]
AID - 10.3390/healthcare11020256 [doi]
PST - epublish
SO  - Healthcare (Basel). 2023 Jan 13;11(2):256. doi: 10.3390/healthcare11020256.