| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Luay Fraiwan, Mohanad Alkhodar. Neonatal sleep stage identification using long short-term memory learning system. Medical & biological engineering & computing. vol 58. issue 6. 2021-04-13. PMID:32281071. |
based on the confusion matrix, the overall true positives percentage reached 95.21%. |
2021-04-13 |
2023-08-13 |
Not clear |
| Kamil Książek, Michał Romaszewski, Przemysław Głomb, Bartosz Grabowski, Michał Cholew. Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks. Sensors (Basel, Switzerland). vol 20. issue 22. 2021-04-08. PMID:33233358. |
we have also presented a model evaluation method based on t-sne and confusion matrix analysis that allows us to detect and eliminate some cases of model undertraining. |
2021-04-08 |
2023-08-13 |
Not clear |
| Jeeyae Choi, Hee-Tae Jung, Anastasiya Ferrell, Seoyoon Woo, Linda Hadda. Machine Learning-Based Nicotine Addiction Prediction Models for Youth E-Cigarette and Waterpipe (Hookah) Users. Journal of clinical medicine. vol 10. issue 5. 2021-04-08. PMID:33801175. |
performance of prediction models was measured by root mean square error (rmse) and confusion matrix. |
2021-04-08 |
2023-08-13 |
human |
| Muhammad Irfan, Muhammad Aksam Iftikhar, Sana Yasin, Umar Draz, Tariq Ali, Shafiq Hussain, Sarah Bukhari, Abdullah Saeed Alwadie, Saifur Rahman, Adam Glowacz, Faisal Althobian. Role of Hybrid Deep Neural Networks (HDNNs), Computed Tomography, and Chest X-rays for the Detection of COVID-19. International journal of environmental research and public health. vol 18. issue 6. 2021-04-08. PMID:33809665. |
the capability and prediction accuracy of the hdnns were calculated using the confusion matrix. |
2021-04-08 |
2023-08-13 |
human |
| Murtaza Ali Kha. An automated and fast system to identify COVID-19 from X-ray radiograph of the chest using image processing and machine learning. International journal of imaging systems and technology. 2021-04-07. PMID:33821097. |
the performance of the system is measured using standard parameters of accuracy and confusion matrix. |
2021-04-07 |
2023-08-13 |
human |
| Niklas Tötsch, Daniel Hoffman. Classifier uncertainty: evidence, potential impact, and probabilistic treatment. PeerJ. Computer science. vol 7. 2021-04-06. PMID:33817044. |
we present an approach to quantify the uncertainty of classification performance metrics, based on a probability model of the confusion matrix. |
2021-04-06 |
2023-08-13 |
Not clear |
| Niklas Tötsch, Daniel Hoffman. Classifier uncertainty: evidence, potential impact, and probabilistic treatment. PeerJ. Computer science. vol 7. 2021-04-06. PMID:33817044. |
the application of our approach is simple and requires only the confusion matrix. |
2021-04-06 |
2023-08-13 |
Not clear |
| Qian Ma, Wenting Han, Shenjin Huang, Shide Dong, Guang Li, Haipeng Che. Distinguishing Planting Structures of Different Complexity from UAV Multispectral Images. Sensors (Basel, Switzerland). vol 21. issue 6. 2021-04-05. PMID:33808967. |
after training the models with the feature subsets, the classification results are evaluated using a confusion matrix. |
2021-04-05 |
2023-08-13 |
Not clear |
| Shixin Cen, Yang Yu, Gang Yan, Ming Yu, Qing Yan. Sparse Spatiotemporal Descriptor for Micro-Expression Recognition Using Enhanced Local Cube Binary Pattern. Sensors (Basel, Switzerland). vol 20. issue 16. 2021-03-25. PMID:32784460. |
through further observation of parameter evaluation and confusion matrix, the sufficiency and effectiveness of the proposed method are proved. |
2021-03-25 |
2023-08-13 |
human |
| Carmen Guzmán-García, Marcos Gómez-Tome, Patricia Sánchez-González, Ignacio Oropesa, Enrique J Góme. Speech-Based Surgical Phase Recognition for Non-Intrusive Surgical Skills' Assessment in Educational Contexts. Sensors (Basel, Switzerland). vol 21. issue 4. 2021-03-22. PMID:33668544. |
the analysis of this model's confusion matrix shows that some phrases are misplaced due to the similarity in the words used. |
2021-03-22 |
2023-08-13 |
Not clear |
| Jing Li, Sen Zhang, Bo Li, Yi Hu, Xiao-Ping Kang, Xiao-Yan Wu, Meng-Ting Huang, Yu-Chang Li, Zhong-Peng Zhao, Cheng-Feng Qin, Tao Jian. Machine Learning Methods for Predicting Human-Adaptive Influenza A Viruses Based on Viral Nucleotide Compositions. Molecular biology and evolution. vol 37. issue 4. 2021-03-18. PMID:31750915. |
the results of the confusion matrix and the area under the receiver operating characteristic curve indicated a high performance of the ml models to predict human adaptation of iavs. |
2021-03-18 |
2023-08-13 |
human |
| R Ramachandran, K Arutchelva. Named entity recognition on bio-medical literature documents using hybrid based approach. Journal of ambient intelligence and humanized computing. 2021-03-17. PMID:33723489. |
the hybrid model is validated with the dictionary and human (optional)to calculate the confusion matrix. |
2021-03-17 |
2023-08-13 |
human |
| Seulah Lee, Yuna Choi, Minchang Sung, Jihyun Bae, Youngjin Cho. A Knitted Sensing Glove for Human Hand Postures Pattern Recognition. Sensors (Basel, Switzerland). vol 21. issue 4. 2021-03-15. PMID:33671966. |
when all mixed data from 10 subjects were utilized for pattern recognition, the average classification expressed by the confusion matrix arrived at 89.5%. |
2021-03-15 |
2023-08-13 |
human |
| Timothy J O'Lear. Relative Sensitivity of Saliva and Upper Airway Swabs for Initial Detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Ambulatory Patients: Rapid Review. The Journal of molecular diagnostics : JMD. vol 23. issue 3. 2021-03-08. PMID:33395576. |
to better understand the relative performance characteristics of saliva and upper airway samples, i performed a rapid systematic review (registered on prospero as crd42020205035), focusing on studies that included at least 20 subjects who provided diagnostic saliva and upper airway samples on the same day, which were tested by nucleic acid amplification methods and for which a confusion matrix could be constructed for based on a composite reference standard. |
2021-03-08 |
2023-08-13 |
human |
| Jamal Abdul Nasir, Chuangyin Dan. Quantitative thresholds based decision support approach for the home health care scheduling and routing problem. Health care management science. vol 23. issue 2. 2021-03-04. PMID:30714070. |
the effectiveness of these thresholds is evaluated by utilizing performance measures of the widely-used confusion matrix. |
2021-03-04 |
2023-08-13 |
Not clear |
| Belal Amin, A A Salama, I M El-Henawy, Khaled Mahfouz, Mona G Gafa. Intelligent Neutrosophic Diagnostic System for Cardiotocography Data. Computational intelligence and neuroscience. vol 2021. 2021-03-04. PMID:33628217. |
the performance measurement of the confusion matrix for the proposed framework is 95.1, 94.95, 95.2, and 95.1 concerning accuracy rate, precision, recall, and |
2021-03-04 |
2023-08-13 |
Not clear |
| Ahmed S Elkorany, Zeinab F Elsharkaw. COVIDetection-Net: A tailored COVID-19 detection from chest radiography images using deep learning. Optik. vol 231. 2021-03-03. PMID:33551492. |
confusion matrix (cm) and receiver operation characteristics (roc) analysis are also used to depict the performance of the proposed model. |
2021-03-03 |
2023-08-13 |
Not clear |
| Dominik Seidel, Peter Annighöfer, Anton Thielman, Quentin Edward Seifert, Jan-Henrik Thauer, Jonas Glatthorn, Martin Ehbrecht, Thomas Kneib, Christian Amme. Predicting Tree Species From 3D Laser Scanning Point Clouds Using Deep Learning. Frontiers in plant science. vol 12. 2021-03-03. PMID:33643364. |
our approach yielded a high classification accuracy (86%) and the confusion matrix revealed that despite rather small sample sizes of the training data for some tree species, classification accuracy was high. |
2021-03-03 |
2023-08-13 |
Not clear |
| Sankaran Rajendran, Ponnumony Vethamony, Fadhil N Sadooni, Hamad Al-Saad Al-Kuwari, Jassim A Al-Khayat, Vashist O Seegobin, Himanshu Govil, Sobhi Nasi. Detection of Wakashio oil spill off Mauritius using Sentinel-1 and 2 data: Capability of sensors, image transformation methods and mapping. Environmental pollution (Barking, Essex : 1987). vol 274. 2021-03-02. PMID:33582596. |
the accuracy of oil spill mapping was assessed by classifying the sar-c data and decorrelated images of the multispectral instrument (msi) data using the parallelepiped supervised algorithm and confusion matrix. |
2021-03-02 |
2023-08-13 |
Not clear |
| Wen-Jun Yin, Chen-Lei Ru, Jie Zheng, Lu Zhang, Ji-Zhong Yan, Hui Zhan. [Fusion of spectrum and image features to identify Glycyrrhizae Radix et Rhizoma from different origins based on hyperspectral imaging technology]. Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica. vol 46. issue 4. 2021-03-02. PMID:33645098. |
in addition, the pls-da model was superior to svc and rf models in terms of classification accuracy and model generalization capability, which were evaluated by confusion matrix and receiver operating characteristic curve(roc). |
2021-03-02 |
2023-08-13 |
Not clear |