A comparative study of support vector machine and logistic  regression for the diagnosis of thyroid dysfunction

Gurram, Deepthi; Rao, M. R. Narasinga

doi:10.14419/ijet.v7i1.1.9714

Cited by 6 publications

(2 citation statements)

References 6 publications

(6 reference statements)

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“…The best accuracy of 98.89% was achieved again by the Decision Tree approach. Logistic regression was used by the collective of authors to predict the patients without thyrotoxicosis and with thyrotoxicosis [14]. The outcomes demonstrate that the logistic regression obtains promising results in classifying regression on thyroid disease diagnosis 98.92%…”

Section: Related Workmentioning

confidence: 99%

Cooperation Between Data Analysts and Medical Experts: A Case Study

Rokošná¹,

Babič²,

Majnarić³

et al. 2020

Lecture Notes in Computer Science

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The medical diagnosis and determine a correct medical procedure represent a comprehensive process that consists of many input information and potential associations. This information can lead to clinical reasoning to resolve a patient's health problem and set the treatment. Effective communication between the medical expert and data analyst can support this process more effectively, dependent on the available data. It is essential to create a shared vocabulary for this cooperation to reduce possible misunderstandings and unnecessary experiments. In our work, we performed exploratory data analysis, statistical tests, correlation analysis, and logistic regression in close cooperation with the participated expert thanks to whom we could verify the achieved results of our models. The collaboration between the medical expert and data analytic requires a lot of communication and explanation from the medical expert because of the correct interpretation of the medical data and its resulting associations. On the other hand, it requires a proper understanding of the task from the data analyst's point of view, a lot of iterations of graphs, and other models, which must be modified to be easy to read and interpret.

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Section: Related Workmentioning

confidence: 99%

Cooperation Between Data Analysts and Medical Experts: A Case Study

Rokošná¹,

Babič²,

Majnarić³

et al. 2020

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…So a lot of scientists have explored diversity of classifiers algorithm like artificial neural network (ANN), logistic regression, fuzzy Cmeans and decision tree etc. to forecast the cholesterol signature motifs [11][12][13][14][15][16][17][18][19]. To investigate the signature motif of cholesterol using the dataset is our focal objectives.…”

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confidence: 99%