- Published
- 2022-03-24
- Venue
- Neural Computing and Applications, vol. 35, no. 22, pp. 16157-16173
- Cited by
- 330
- Open access
- Yes, hybrid
- DOI
- 10.1007/s00521-022-07049-z
- PubMed
- 35345556
Abstract
This paper proposes an e-diagnosis system based on machine learning (ML) algorithms to be implemented on the Internet of Medical Things (IoMT) environment, particularly for diagnosing diabetes mellitus (type 2 diabetes). However, the ML applications tend to be mistrusted because of their inability to show the internal decision-making process, resulting in slow uptake by end-users within certain healthcare sectors. This research delineates the use of three interpretable supervised ML models: Naïve Bayes classifier, random forest classifier, and J48 decision tree models to be trained and tested using the Pima Indians diabetes dataset in R programming language. The performance of each algorithm is analyzed to determine the one with the best accuracy, precision, sensitivity, and specificity. An assessment of the decision process is also made to improve the model. It can be concluded that a Naïve Bayes model works well with a more fine-tuned selection of features for binary classification, while random forest works better with more features.
Cite this paper
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- APA 7
Chang, V. I. C., Bailey, J., Xu, Q. A., & Sun, Z. (2022). Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms. Neural Computing and Applications, 35(22), 16157–16173. https://doi.org/10.1007/s00521-022-07049-z
- MLA 9
Chang, Victor I. C., et al. "Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms." Neural Computing and Applications, vol. 35, no. 22, 2022, pp. 16157–16173, https://doi.org/10.1007/s00521-022-07049-z.
- Chicago
Chang, Victor I. C., Jozeene Bailey, Qianwen Ariel Xu, and Zhili Sun. "Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms." Neural Computing and Applications 35, no. 22 (2022): 16157–16173. https://doi.org/10.1007/s00521-022-07049-z.
- GOST
Chang V. I. C., Bailey J., Xu Q. A. [и др.] Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms // Neural Computing and Applications. — 2022. — Vol. 35, № 22. — P. 16157–16173. — URL: https://doi.org/10.1007/s00521-022-07049-z
- BibTeX
@article{chang2022pima, title = {{Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms}}, author = {Victor I. C. Chang and Jozeene Bailey and Qianwen Ariel Xu and Zhili Sun}, journal = {Neural Computing and Applications}, year = {2022}, volume = {35}, number = {22}, pages = {16157--16173}, doi = {10.1007/s00521-022-07049-z}, url = {https://doi.org/10.1007/s00521-022-07049-z} }- RIS
TY - JOUR AU - Chang, Victor I. C. AU - Bailey, Jozeene AU - Xu, Qianwen Ariel AU - Sun, Zhili TI - Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms JO - Neural Computing and Applications VL - 35 IS - 22 SP - 16157 EP - 16173 PY - 2022 DA - 2022/03/24 DO - 10.1007/s00521-022-07049-z UR - https://doi.org/10.1007/s00521-022-07049-z ER -
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