PMID- 35875742
OWN - NLM
STAT- MEDLINE
DCOM- 20220726
LR  - 20220726
IS  - 1687-5273 (Electronic)
IS  - 1687-5265 (Print)
VI  - 2022
DP  - 2022
TI  - Blended Ensemble Learning Prediction Model for Strengthening Diagnosis and 
      Treatment of Chronic Diabetes Disease.
PG  - 4451792
LID - 10.1155/2022/4451792 [doi]
LID - 4451792
AB  - Diabetes mellitus (DM), commonly known as diabetes, is a collection of metabolic 
      illnesses characterized by persistently high blood sugar levels. The signs of 
      elevated blood sugar include increased hunger, frequent urination, and increased 
      thirst. If DM is not treated properly, it may lead to several complications. 
      Diabetes is caused by either insufficient insulin production by the pancreas or 
      an insufficient insulin response by the body's cells. Every year, 1.6 million 
      individuals die from this disease. The objective of this research work is to use 
      relevant features to construct a blended ensemble learning (EL)-based forecasting 
      system and find the optimal classifier for comparing clinical outputs. The EL 
      based on Bayesian networks and radial basis functions has been proposed in this 
      article. The performances of five machine learning (ML) techniques, namely, 
      logistic regression (LR), decision tree (DT) classifier, support vector machine 
      (SVM), K-nearest neighbors (KNN), and random forest (RF), are compared with the 
      proposed EL technique. Experiments reveal that the EL method performs better than 
      the existing ML approaches in predicting diabetic illness, with the remarkable 
      accuracy of 97.11%. The proposed ensemble learning could be useful in assisting 
      specialists in accurately diagnosing diabetes and assisting patients in receiving 
      the appropriate therapy.
CI  - Copyright (c) 2022 T. R. Mahesh et al.
FAU - Mahesh, T R
AU  - Mahesh TR
AUID- ORCID: 0000-0002-5589-8992
AD  - Department of Computer Science and Engineering, Faculty of Engineering and 
      Technology, JAIN (Deemed-to-be University), Bangalore, India.
FAU - Kumar, Dhilip
AU  - Kumar D
AUID- ORCID: 0000-0003-2274-8127
AD  - Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. 
      Sagunthala R&D Institute of Science and Technology, Chennai, India.
FAU - Vinoth Kumar, V
AU  - Vinoth Kumar V
AUID- ORCID: 0000-0003-1070-3212
AD  - Department of Computer Science and Engineering, Faculty of Engineering and 
      Technology, JAIN (Deemed-to-be University), Bangalore, India.
FAU - Asghar, Junaid
AU  - Asghar J
AUID- ORCID: 0000-0003-2218-0789
AD  - Faculty of Pharmacy, Gomal University, Dera Ismail Khan 29050, Khyber 
      Pakhtunkhwa, Pakistan.
FAU - Mekcha Bazezew, Banchigize
AU  - Mekcha Bazezew B
AUID- ORCID: 0000-0002-4552-6677
AD  - Department of Electrical and Computer Engineering, Wollo University, Ethiopia.
FAU - Natarajan, Rajesh
AU  - Natarajan R
AUID- ORCID: 0000-0003-1255-9621
AD  - Department of Information Technology, University of Technology and Applied 
      Science, Shinas. Sultanate of Oman, Oman.
FAU - Vivek, V
AU  - Vivek V
AUID- ORCID: 0000-0003-2748-2890
AD  - Department of Computer Science and Engineering, Faculty of Engineering and 
      Technology, JAIN (Deemed-to-be University), Bangalore, India.
LA  - eng
PT  - Journal Article
DEP - 20220714
PL  - United States
TA  - Comput Intell Neurosci
JT  - Computational intelligence and neuroscience
JID - 101279357
RN  - 0 (Blood Glucose)
RN  - 0 (Insulins)
SB  - IM
MH  - Bayes Theorem
MH  - Blood Glucose
MH  - *Diabetes Mellitus/diagnosis/therapy
MH  - Humans
MH  - *Insulins
MH  - Machine Learning
MH  - Support Vector Machine
PMC - PMC9303104
COIS- The authors declare that they have no conflicts of interest.
EDAT- 2022/07/26 06:00
MHDA- 2022/07/27 06:00
PMCR- 2022/07/14
CRDT- 2022/07/25 04:15
PHST- 2022/05/22 00:00 [received]
PHST- 2022/06/24 00:00 [accepted]
PHST- 2022/07/25 04:15 [entrez]
PHST- 2022/07/26 06:00 [pubmed]
PHST- 2022/07/27 06:00 [medline]
PHST- 2022/07/14 00:00 [pmc-release]
AID - 10.1155/2022/4451792 [doi]
PST - epublish
SO  - Comput Intell Neurosci. 2022 Jul 14;2022:4451792. doi: 10.1155/2022/4451792. 
      eCollection 2022.