| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Shuang Zhou, Li Pen. Applying Bayesian Belief Networks to Assess Alpine Grassland Degradation Risks: A Case Study in Northwest Sichuan, China. Frontiers in plant science. vol 12. 2021-11-23. PMID:34804106. |
the obtained result showed that the accuracies based on the confusion matrix of the slope of ndvi change (ndvis), shrub-encroached grasslands, and grassland degradation indicators in the bbn model were 85.27, 88.99, and 74.37%, respectively. |
2021-11-23 |
2023-08-13 |
Not clear |
| Veerayuth Kittichai, Theerakamol Pengsakul, Kemmapon Chumchuen, Yudthana Samung, Patchara Sriwichai, Natthaphop Phatthamolrat, Teerawat Tongloy, Komgrit Jaksukam, Santhad Chuwongin, Siridech Boonsan. Deep learning approaches for challenging species and gender identification of mosquito vectors. Scientific reports. vol 11. issue 1. 2021-11-22. PMID:33649429. |
thirteen classes were detected with an accuracy of 100% based on a confusion matrix. |
2021-11-22 |
2023-08-13 |
Not clear |
| Vanessa De Araujo Faria, Mehran Azimbagirad, Gustavo Viani Arruda, Juliana Fernandes Pavoni, Joaquim Cezar Felipe, Elza Maria Carneiro Mendes Ferreira Dos Santos, Luiz Otavio Murta Junio. Prediction of Radiation-Related Dental Caries Through PyRadiomics Features and Artificial Neural Network on Panoramic Radiography. Journal of digital imaging. vol 34. issue 5. 2021-11-17. PMID:34254199. |
to evaluate the method, we calculated the confusion matrix, receiver operating characteristic (roc), and area under curve (auc), as well as a comparison with recent methods. |
2021-11-17 |
2023-08-13 |
Not clear |
| Hamza Osman Ilhan, Gorkem Serbes, Nizamettin Aydi. Decision and feature level fusion of deep features extracted from public COVID-19 data-sets. Applied intelligence (Dordrecht, Netherlands). 2021-11-13. PMID:34764623. |
the obtained accuracy values and confusion matrix based evaluation criteria were presented for three progressively created data-sets. |
2021-11-13 |
2023-08-13 |
Not clear |
| Emily Daykin, Nicole Fleischer, Magy Abdelwahab, Nehal Hassib, Raphael Schiffmann, Emory Ryan, Ellen Sidransk. Investigation of a dysmorphic facial phenotype in patients with Gaucher disease types 2 and 3. Molecular genetics and metabolism. vol 134. issue 3. 2021-11-12. PMID:34663554. |
outputs included a composite photo of each cohort and either a receiver operating characteristic curve or a confusion matrix. |
2021-11-12 |
2023-08-13 |
Not clear |
| Winnie Y Zou, Binu E Enchakalody, Peng Zhang, Nidhi Shah, Sameer D Saini, Nicholas C Wang, Stewart C Wang, Grace L S. Automated Measurements of Body Composition in Abdominal CT Scans Using Artificial Intelligence Can Predict Mortality in Patients With Cirrhosis. Hepatology communications. vol 5. issue 11. 2021-11-10. PMID:34558818. |
to assess model performance, we used the confusion matrix and calculated the mean accuracy of 0.977 ± 0.02 (0.975 ± 0.018 for the training and test sets, respectively). |
2021-11-10 |
2023-08-13 |
Not clear |
| Amarit Tansawet, Panupong Nakchuai, Suphakarn Techapongsatorn, Pakkapol Sukhvibul, Sermkiat Lola. Prediction of seroma after total mastectomy using an artificial neural network algorithm. Breast disease. vol 41. issue 1. 2021-11-08. PMID:34250921. |
the model performance was assessed by a confusion matrix in the validating data set. |
2021-11-08 |
2023-08-13 |
human |
| Vaibhav Gurunathan, John Hamre, Dmitri K Klimov, Mohsin Saleet Jafr. Data Mining of Molecular Simulations Suggest Key Amino Acid Residues for Aggregation, Signaling and Drug Action. Biomolecules. vol 11. issue 10. 2021-11-08. PMID:34680174. |
the test and score module coupled with the confusion matrix module analyzed data with calculations of specificity and sensitivity. |
2021-11-08 |
2023-08-13 |
Not clear |
| Lihui Wang, Zhenjia Chen, Yonghui Zhan. Wireless signal modulation identification method based on RF I/Q data distribution. Scientific reports. vol 11. issue 1. 2021-11-05. PMID:34725393. |
according to the result of the confusion matrix, the weight of the model is adjusted. |
2021-11-05 |
2023-08-13 |
Not clear |
| Dong Jin Park, Min Woo Park, Homin Lee, Young-Jin Kim, Yeongsic Kim, Young Hoon Par. Development of machine learning model for diagnostic disease prediction based on laboratory tests. Scientific reports. vol 11. issue 1. 2021-10-29. PMID:33828178. |
we used a confusion matrix and analyzed feature importance using the shap value method. |
2021-10-29 |
2023-08-13 |
Not clear |
| Sikandar Ali, Ali Hussain, Satyabrata Aich, Moo Suk Park, Man Pyo Chung, Sung Hwan Jeong, Jin Woo Song, Jae Ha Lee, Hee Cheol Ki. A Soft Voting Ensemble-Based Model for the Early Prediction of Idiopathic Pulmonary Fibrosis (IPF) Disease Severity in Lungs Disease Patients. Life (Basel, Switzerland). vol 11. issue 10. 2021-10-26. PMID:34685461. |
fourth, the performance of the proposed model was evaluated by calculating the accuracy, auc, confusion matrix, precision, recall, and f1-score. |
2021-10-26 |
2023-08-13 |
human |
| Sahar Jorjandi, Zahra Amini, Gerlind Plonka, Hossein Rabban. Statistical modeling of retinal optical coherence tomography using the Weibull mixture model. Biomedical optics express. vol 12. issue 9. 2021-10-26. PMID:34692195. |
the confusion matrix demonstrates the impact of the proposed model in our preliminary study on the oct classification problem. |
2021-10-26 |
2023-08-13 |
Not clear |
| Christiane V Löhr, Susanne M Stieger-Vanegas, Jesse L Terry, Milan Milovancev, Jan Medloc. Targeting Peritumoral Lesions Identified by Computed Tomography and Magnetic Resonance Imaging in Feline Injection-Site Sarcomas for Microscopic Examination. Veterinary pathology. vol 58. issue 5. 2021-10-25. PMID:33969752. |
computation of a simple confusion matrix yielded fair sensitivity (70.4%) and low specificity (59.7%) for prediction of ptiil by histologic findings. |
2021-10-25 |
2023-08-13 |
Not clear |
| Paolo Sorino, Angelo Campanella, Caterina Bonfiglio, Antonella Mirizzi, Isabella Franco, Antonella Bianco, Maria Gabriella Caruso, Giovanni Misciagna, Laura R Aballay, Claudia Buongiorno, Rosalba Liuzzi, Anna Maria Cisternino, Maria Notarnicola, Marisa Chiloiro, Francesca Fallucchi, Giovanni Pascoschi, Alberto Rubén Osell. Development and validation of a neural network for NAFLD diagnosis. Scientific reports. vol 11. issue 1. 2021-10-16. PMID:34642390. |
the percentage of accuracy, area under the roc curve, confusion matrix, positive (ppv) and negative predicted value (npv) values, precision, recall and f1-score were verified. |
2021-10-16 |
2023-08-13 |
human |
| Basheer Husham Ali, Nasri Sulaiman, Syed Abdul Rahman Al-Haddad, Rodziah Atan, Siti Lailatul Mohd Hassan, Mokhalad Alghrair. Identification of Distributed Denial of Services Anomalies by Using Combination of Entropy and Sequential Probabilities Ratio Test Methods. Sensors (Basel, Switzerland). vol 21. issue 19. 2021-10-14. PMID:34640773. |
the metric of a confusion matrix was used to compare the esprt results with the results of other methods. |
2021-10-14 |
2023-08-13 |
Not clear |
| Abdulah Jeza Aljohani, Junaid Shuja, Waleed Alasmary, Abdulaziz Alashaik. Evaluating the Dynamics of Bluetooth Low Energy Based COVID-19 Risk Estimation for Educational Institutes. Sensors (Basel, Switzerland). vol 21. issue 19. 2021-10-14. PMID:34640986. |
we analyze the accuracy of the ml classifiers in terms of f-score, receiver operating characteristic (roc) curve, and confusion matrix. |
2021-10-14 |
2023-08-13 |
Not clear |
| Ryoungwoo Jang, Jae Ho Choi, Namkug Kim, Jae Suk Chang, Pil Whan Yoon, Chul-Ho Ki. Prediction of osteoporosis from simple hip radiography using deep learning algorithm. Scientific reports. vol 11. issue 1. 2021-10-13. PMID:34620976. |
we calculated the confusion matrix and evaluated the accuracy, sensitivity, specificity, positive predictive value (ppv), and negative predictive value (npv). |
2021-10-13 |
2023-08-13 |
Not clear |
| R Karthiyayini, N Shenbagavadiv. Retinal Image Analysis for Ocular Disease Prediction Using Rule Mining Algorithms. Interdisciplinary sciences, computational life sciences. vol 13. issue 3. 2021-10-01. PMID:32514844. |
the results of confusion matrix have shown that there was 93% prediction accuracy which was higher than the predictive values of other algorithms. |
2021-10-01 |
2023-08-13 |
Not clear |
| Antonio Alarcón-Paredes, Iris P Guzmán-Guzmán, Diana E Hernández-Rosales, José E Navarro-Zarza, Jessica Cantillo-Negrete, René E Cuevas-Valencia, Gustavo A Alons. Computer-aided diagnosis based on hand thermal, RGB images, and grip force using artificial intelligence as screening tool for rheumatoid arthritis in women. Medical & biological engineering & computing. vol 59. issue 2. 2021-09-29. PMID:33420616. |
in this test, an accuracy of 94.7% was obtained using rgb images; the confusion matrix revealed our system provides a correct diagnosis for all participants and failed in only two of them (5.3%). |
2021-09-29 |
2023-08-13 |
human |
| Duc-Phong Nguyen, Marie-Christine Ho Ba Tho, Tien-Tuan Da. Enhanced facial expression recognition using 3D point sets and geometric deep learning. Medical & biological engineering & computing. vol 59. issue 6. 2021-09-29. PMID:34028664. |
finally, the developed model was evaluated using the recognition rate and confusion matrix. |
2021-09-29 |
2023-08-13 |
human |