| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Mohamed Karim El Oufir, Karem Chokmani, Anas El Alem, Hachem Agili, Monique Bernie. Seasonal Snowpack Classification Based on Physical Properties Using Near-Infrared Proximal Hyperspectral Data. Sensors (Basel, Switzerland). vol 21. issue 16. 2021-08-31. PMID:34450701. |
finally, a confusion matrix was calculated to evaluate the accuracy of the classification. |
2021-08-31 |
2023-08-13 |
Not clear |
| Xiran Jiang, Jiaxin Li, Yangyang Kan, Tao Yu, Shijie Chang, Xianzheng Sha, Hairong Zheng, Yahong Luo, Shanshan Wan. MRI Based Radiomics Approach With Deep Learning for Prediction of Vessel Invasion in Early-Stage Cervical Cancer. IEEE/ACM transactions on computational biology and bioinformatics. vol 18. issue 3. 2021-08-30. PMID:31905143. |
predictive performances were evaluated using receiver operating characteristic (roc) curve and confusion matrix analysis, with the dce-t1 showing more discriminative results than t2wi mri. |
2021-08-30 |
2023-08-13 |
Not clear |
| Wei Song, Huanhuan L. A new method for acquiring long-term high-precision spatial data on rural settlements. MethodsX. vol 8. 2021-08-26. PMID:34434772. |
we describe a new method to confirm validation samples in this article and use a confusion matrix to verify data accuracy. |
2021-08-26 |
2023-08-13 |
Not clear |
| Wei Song, Huanhuan L. A new method for acquiring long-term high-precision spatial data on rural settlements. MethodsX. vol 8. 2021-08-26. PMID:34434772. |
the kappa value yielded in this approach was 0.97; the method described here can be used in the future for the acquisition of high-precision spatial data from historical rural settlements.•decrypted keyhole military satellite images were used as a data source to obtain high-precision information regarding historical rural settlements.•the new method proposed in this article was used to verify the accuracy of sample data and to solve the ongoing problem that historical image land use often cannot be verified.•result accuracy was verified using functions in arcgis 10.4 to create accuracy assessment points, update them, and compute a confusion matrix. |
2021-08-26 |
2023-08-13 |
Not clear |
| Seyed Mortaza Mousavi, Akbar Asgharzadeh-Bonab, Ramin Ranjbarzade. Time-Frequency Analysis of EEG Signals and GLCM Features for Depth of Anesthesia Monitoring. Computational intelligence and neuroscience. vol 2021. 2021-08-24. PMID:34422035. |
we obtain the accuracy and confusion matrix of the proposed method. |
2021-08-24 |
2023-08-13 |
Not clear |
| Naomar Almeida-Filh. [Health inequalities: new theoretical perspectives]. Salud colectiva. vol 16. 2021-08-23. PMID:32574463. |
thirdly, i present a semantic matrix proposed for the difference-distinction-inequality-inequity-iniquity series to help reduce the existing terminological confusion. |
2021-08-23 |
2023-08-13 |
Not clear |
| Balaji E, Brindha D, Vinodh Kumar Elumalai, Umesh . Data-driven gait analysis for diagnosis and severity rating of Parkinson's disease. Medical engineering & physics. vol 91. 2021-08-23. PMID:34074466. |
the performance of the classifiers, assessed using the confusion matrix and parallel coordinate plots, highlights that svm can result in a classification accuracy of 98.4%. |
2021-08-23 |
2023-08-13 |
Not clear |
| David Dreizin, Florian Goldmann, Christina LeBedis, Alexis Boscak, Matthew Dattwyler, Uttam Bodanapally, Guang Li, Stephan Anderson, Andreas Maier, Mathias Unberat. An Automated Deep Learning Method for Tile AO/OTA Pelvic Fracture Severity Grading from Trauma whole-Body CT. Journal of digital imaging. vol 34. issue 1. 2021-08-19. PMID:33479859. |
confusion matrix results were derived, anchored to peak matthews correlation coefficient (mcc). |
2021-08-19 |
2023-08-13 |
Not clear |
| Farah Masood, Maisha Farzana, Shanker Nesathurai, Hussein A Abdulla. Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury. Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine. vol 234. issue 9. 2021-08-18. PMID:32605433. |
a confusion matrix and five other statistical metrics (sensitivity, specificity, precision, accuracy, and f-measure) were used to evaluate the performance of the generated classifiers. |
2021-08-18 |
2023-08-13 |
Not clear |
| Nicolás Amigo, Alvaro Valencia, Wei Wu, Sourav Patnaik, Ender Fino. Cerebral aneurysm rupture status classification using statistical and machine learning methods. Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine. vol 235. issue 6. 2021-08-18. PMID:33685288. |
the performance of each parameter was inspected using hypothesis testing, accuracy, confusion matrix, and the area under the receiver operating characteristic curve. |
2021-08-18 |
2023-08-13 |
Not clear |
| Soumya Ranjan Nayak, Janmenjoy Nayak, Utkarsh Sinha, Vaibhav Arora, Uttam Ghosh, Suresh Chandra Satapath. An Automated Lightweight Deep Neural Network for Diagnosis of COVID-19 from Chest X-ray Images. Arabian journal for science and engineering. 2021-08-17. PMID:34395157. |
apart from this, several other performance measures like tenfold cross-validation, confusion matrix, evaluation metrics, sarea under the receiver operating characteristics, kappa score and mathew's correlation, and grad-cam heat map have been used to assess the efficacy of the proposed model. |
2021-08-17 |
2023-08-13 |
Not clear |
| Omar F AlThuwaynee, Sang-Wan Kim, Mohamed A Najemaden, Ali Aydda, Abdul-Lateef Balogun, Moatasem M Fayyadh, Hyuck-Jin Par. Demystifying uncertainty in PM10 susceptibility mapping using variable drop-off in extreme-gradient boosting (XGB) and random forest (RF) algorithms. Environmental science and pollution research international. vol 28. issue 32. 2021-08-13. PMID:33834339. |
these were assessed against utility criteria such as a confusion matrix of overall accuracy, quantity of variables, processing delay, degree of overfitting, importance distribution, and area under the receiver operating characteristic curve (roc). |
2021-08-13 |
2023-08-13 |
Not clear |
| L S Suma, H S Anand, S S Vinod Chandr. Nature inspired optimization model for classification and severity prediction in COVID-19 clinical dataset. Journal of ambient intelligence and humanized computing. 2021-08-10. PMID:34367354. |
the confusion matrix and the precision-recall values (0.96 and 0.97) of the binary classifier indicate the classifier's efficiency in predicting positive cases correctly. |
2021-08-10 |
2023-08-13 |
bee |
| Meenu Gupta, Hao Wu, Simrann Arora, Akash Gupta, Gopal Chaudhary, Qiaozhi Hu. Gene Mutation Classification through Text Evidence Facilitating Cancer Tumour Detection. Journal of healthcare engineering. vol 2021. 2021-08-10. PMID:34367540. |
the accuracy score of all the proposed classifiers is evaluated by using the confusion matrix. |
2021-08-10 |
2023-08-13 |
Not clear |
| Yang Wang, Moyang L. Quantitative Evaluation of Plant and Modern Urban Landscape Spatial Scale Based on Multiscale Convolutional Neural Network. Computational intelligence and neuroscience. vol 2021. 2021-08-03. PMID:34335725. |
the results show that the overall kappa coefficient is 0.91 and the classification accuracy is 93% by calculating the confusion matrix, production accuracy, and user accuracy. |
2021-08-03 |
2023-08-13 |
Not clear |
| Xue L. Design and Implementation of Human Motion Recognition Information Processing System Based on LSTM Recurrent Neural Network Algorithm. Computational intelligence and neuroscience. vol 2021. 2021-08-02. PMID:34326865. |
the final results show that the performance of lstm recurrent neural network is better than the traditional algorithm, the accuracy can reach 0.980, and the confusion matrix results show that the recognition of human motion by the system can reach 85 points to the greatest extent. |
2021-08-02 |
2023-08-13 |
human |
| Chaahat, Naveen Kumar Gondhi, Parveen Kumar Lehan. An Evolutionary Approach for the Enhancement of Dermatological Images and Their Classification Using Deep Learning Models. Journal of healthcare engineering. vol 2021. 2021-07-31. PMID:34326979. |
the results were further analyzed using a confusion matrix and |
2021-07-31 |
2023-08-13 |
human |
| Shahenda Sarhan, Aida A Nasr, Mahmoud Y Sham. Multipose Face Recognition-Based Combined Adaptive Deep Learning Vector Quantization. Computational intelligence and neuroscience. vol 2020. 2021-07-28. PMID:33029115. |
finally, the comparison is empirically performed using confusion matrix to ensure the reliability and robustness of the proposed system compared to the state-of art. |
2021-07-28 |
2023-08-13 |
Not clear |
| Rohit Bharti, Aditya Khamparia, Mohammad Shabaz, Gaurav Dhiman, Sagar Pande, Parneet Sing. Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning. Computational intelligence and neuroscience. vol 2021. 2021-07-27. PMID:34306056. |
various promising results are achieved and are validated using accuracy and confusion matrix. |
2021-07-27 |
2023-08-13 |
Not clear |
| Yixu Huang, Iyll-Joon Doh, Euiwon Ba. Design and Validation of a Portable Machine Learning-Based Electronic Nose. Sensors (Basel, Switzerland). vol 21. issue 11. 2021-07-07. PMID:34200440. |
as a proof of concept, four different types of wine samples and three different oil samples were classified, and the training model reported 100% and 98% accuracy based on the confusion matrix analysis, respectively. |
2021-07-07 |
2023-08-13 |
human |