Identifying diseases and diagnosis using machine learning

Iswanto Iswanto, E. Laxmi Lydia, K. Shankar, Phong Thanh Nguyen, Wahidah Hashim, Andino Maseleno

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The method that is use to optimize the criterion efficiency that depend on the previous experience is known as machine learning. By using the statistics theory it creates the mathematical model, and its major work is to surmise from the examples gave. To take the data straightforwardly from the information the approach uses computational methods. For recognize and identify the disease correctly a pattern is very necessary in Diagnosis recognition of disease. for creating the different models machine learning is used, this model can use for prediction of output and this output is depend on the input that is related to the data which previously used. For curing any disease it is very important to identify and detect that disease. For classify the disease classification algorithms are used. It uses are many dimensionality reduction algorithms and classification algorithms. Without externally modified the computer can learn with the help of the machine learning. For taking the best fit from the observation set the hypothesis is selected. Multi-dimensional and high dimensional are used in machine learning. By using machine learning automatic and classy algorithms can build.

Original languageEnglish
Pages (from-to)978-981
Number of pages4
JournalInternational Journal of Engineering and Advanced Technology
Volume8
Issue number6 Special Issue 2
DOIs
Publication statusPublished - Aug 2019

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Engineering(all)
  • Computer Science Applications

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    Iswanto, I., Laxmi Lydia, E., Shankar, K., Nguyen, P. T., Hashim, W., & Maseleno, A. (2019). Identifying diseases and diagnosis using machine learning. International Journal of Engineering and Advanced Technology, 8(6 Special Issue 2), 978-981. https://doi.org/10.35940/ijeat.F1297.0886S219