Titlebook: Computational Intelligence for Clinical Diagnosis; Ferdin Joe John Joseph,Valentina Emilia Balas,R. R Book 2023 European Alliance for Inno

solidity

书目名称Computational Intelligence for Clinical Diagnosis影响因子(影响力)




书目名称Computational Intelligence for Clinical Diagnosis影响因子(影响力)学科排名




书目名称Computational Intelligence for Clinical Diagnosis网络公开度




书目名称Computational Intelligence for Clinical Diagnosis网络公开度学科排名




书目名称Computational Intelligence for Clinical Diagnosis被引频次




书目名称Computational Intelligence for Clinical Diagnosis被引频次学科排名




书目名称Computational Intelligence for Clinical Diagnosis年度引用




书目名称Computational Intelligence for Clinical Diagnosis年度引用学科排名




书目名称Computational Intelligence for Clinical Diagnosis读者反馈




书目名称Computational Intelligence for Clinical Diagnosis读者反馈学科排名

退出可食用

Radio-Histologie und Radio-Histopathologie, (SVM) algorithms are investigated in the context of the diagnosis of hypothyroidism and hyperthyroidism, respectively. The CNN classifier outperforms the SVM classifier with an accuracy of 89% and a precision of 87%, resulting in more accurate and consistent outcomes.

Inordinate

https://doi.org/10.1007/978-3-662-42341-7m various modalities are registered, and noise removal is done with the help of preprocessing. Every preprocessed image was integrated by means of partition towards low as well as high-frequency bands. Finally, every decomposed coefficient ensures fusion using appropriate rules.

Terminal

灌输

Efficient Method for Predicting Thyroid Disease Classification using Convolutional Neural Network w (SVM) algorithms are investigated in the context of the diagnosis of hypothyroidism and hyperthyroidism, respectively. The CNN classifier outperforms the SVM classifier with an accuracy of 89% and a precision of 87%, resulting in more accurate and consistent outcomes.

滔滔不绝地讲

Multimodality Brain Tumor Image Fusion Using Wavelet and Contourlet Transformation,m various modalities are registered, and noise removal is done with the help of preprocessing. Every preprocessed image was integrated by means of partition towards low as well as high-frequency bands. Finally, every decomposed coefficient ensures fusion using appropriate rules.

滔滔不绝地讲

Prediction and Classification of Aerosol Deposition in Lung Using CT Scan Images,aberrant CT scan results in an increase in diagnostic precision. When projecting a three-dimensional image of a region of interest, certain parameters, including reflection coefficients, mass density, and tissue impedance, are taken into consideration (ROI).

Cardiac-Output

LASH

https://doi.org/10.1007/978-3-642-95173-2 the diagnosis of thyroid problems was put to the test with the help of the original dataset that was gathered from the Sawai Man Singh (SMS) hospital in India. The results show that the SVM classifier exceeds logistic regression with a precision of 84% and an overall accuracy of 86%.

动物

https://doi.org/10.1007/978-3-662-42341-7h analysis will pave the way for clinical framework advancement and cancer patient treatment. In this study, a sodium alginate phantom for breast thermogram evaluation is generated, and thermal screenshots are captured with a thermal imaging camera with the further assessment that can be traced back to standard methods.