| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Ronpichai Chokesuwattanaskul, Aisawan Petchlorlian, Piyoros Lertsanguansinchai, Paramaporn Suttirut, Narut Prasitlumkum, Suphot Srimahachota, Wacin Buddhar. Machine Learning-Based Predictive Model of Aortic Valve Replacement Modality Selection in Severe Aortic Stenosis Patients. Medical sciences (Basel, Switzerland). vol 12. issue 1. 2024-01-22. PMID:38249079. |
the accuracy of the prediction on confusion matrix was used to assess model performance. |
2024-01-22 |
2024-01-24 |
Not clear |
| Yulin Sun, Weisheng Dong, Xin Li, Le Dong, Guangming Shi, Xuemei Xi. TransVQA: Transferable Vector Quantization Alignment for Unsupervised Domain Adaptation. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. vol PP. 2024-01-18. PMID:38231815. |
in this paper, we present a novel model named transferable vector quantization alignment for unsupervised domain adaptation (transvqa), which integrates the transferable transformer-based feature extractor (trans), vector quantization domain alignment (vqa), and mutual information weighted maximization confusion matrix (mimc) of intra-class discrimination into a unified domain adaptation framework. |
2024-01-18 |
2024-01-20 |
Not clear |
| Zeyuan Zhang, Zheyuan Chang, Jingyun Huang, Geng Leng, Wenbo Xu, Yuewu Wang, Zhenwei Xie, Jiawei Yan. Enhancing soil texture classification with multivariate scattering correction and residual neural networks using visible near-infrared spectra. Journal of environmental management. vol 352. 2024-01-18. PMID:38237335. |
the resnet model demonstrated a marked superiority in classifying datasets with similar features, as observed by the confusion matrix analysis. |
2024-01-18 |
2024-01-21 |
Not clear |
| Yongtian Cheng, Pablo A Pérez-Díaz, K V Petrides, Johnson L. Monte Carlo simulation with confusion matrix paradigm - A sample of internal consistency indices. Frontiers in psychology. vol 14. 2024-01-15. PMID:38222847. |
monte carlo simulation with confusion matrix paradigm - a sample of internal consistency indices. |
2024-01-15 |
2024-01-17 |
Not clear |
| Yongtian Cheng, Pablo A Pérez-Díaz, K V Petrides, Johnson L. Monte Carlo simulation with confusion matrix paradigm - A sample of internal consistency indices. Frontiers in psychology. vol 14. 2024-01-15. PMID:38222847. |
this present study proposes a design based on a common statistic evaluation procedure in psychology and machine learning, using a confusion matrix with four cells: true positive, true negative, false negative modified, and false positive modified. |
2024-01-15 |
2024-01-17 |
Not clear |
| Coby Penso, Lior Frenkel, Jacob Goldberge. Confidence Calibration of a Medical Imaging Classification System that is Robust to Label Noise. IEEE transactions on medical imaging. vol PP. 2024-01-15. PMID:38224509. |
we draw on the fact that the confusion matrix of the noisy labels can be expressed as the matrix product between the confusion matrix of the clean labels and the label noises. |
2024-01-15 |
2024-01-18 |
Not clear |
| Hongbo Chen, Eldan Cohen, Dulaney Wilson, Myrtede Alfte. Improving Patient Safety Event Report Classification with Machine Learning and Contextual Text Representation. Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting. vol 67. issue 1. 2024-01-12. PMID:38213998. |
furthermore, the confusion matrix of the best classifier exposes latent deficiencies in the pse reports' classification taxonomy, such as the multi-class nature of pse and conceptually related event types. |
2024-01-12 |
2024-01-14 |
Not clear |
| Qingzhen Sun, Jinguang L. A method for extracting small water bodies based on DEM and remote sensing images. Scientific reports. vol 14. issue 1. 2024-01-09. PMID:38191904. |
taking the water bodies in xinyang city as an example, the overall accuracy of the confusion matrix was the highest, with an overall accuracy of 93.0% compared with the traditional index method. |
2024-01-09 |
2024-01-10 |
Not clear |
| Zepeng Wang, Jianping Chen, Zechen Lian, Fei Li, Lu Pang, Yabo Xi. Influence of buffer distance on environmental geological hazard susceptibility assessment. Environmental science and pollution research international. 2024-01-09. PMID:38194173. |
the results show that through the confusion matrix and roc curve test, the accuracy of the model increases first and then decreases with the increase of buffer distance. |
2024-01-09 |
2024-01-10 |
Not clear |
| Alex Glineur, Katherine Nott, Philippe Carbonnelle, Sébastien Ronkart, Thomas Pollet, Giorgia Purcar. Occurrence and environmental risk assessment of 4 estrogenic compounds in surface water in Belgium in the frame of the EU Watch List. Environmental science and pollution research international. 2023-12-28. PMID:38153577. |
the use of a confusion matrix was investigated to try to predict the risk posed by e2, ee2, based on the concentration of e1. |
2023-12-28 |
2023-12-30 |
Not clear |
| Jiacan Xu, Donglin Li, Peng Zhou, Chunsheng Li, Zinan Wang, Shenghao Ton. A multi-band centroid contrastive reconstruction fusion network for motor imagery electroencephalogram signal decoding. Mathematical biosciences and engineering : MBE. vol 20. issue 12. 2023-12-21. PMID:38124568. |
moreover, the classification effect of sub-band features of different subjects is verified by comparison tests, the category propensity of different sub-band features is verified by confusion matrix tests and the distribution in different classes of each sub-band feature and fused feature are showed by visual analysis, revealing the importance of different sub-band features for the eeg-based mi classification task. |
2023-12-21 |
2023-12-23 |
human |
| João Paulo N Lopes, Wilson R Nascimento, Cesar G Diniz, Pedro Walfir M Souza-Filh. Mangrove changes over the past decade in South and Southeast Brazil using spaceborne optical and SAR imagery. Anais da Academia Brasileira de Ciencias. vol 95. issue suppl 2. 2023-12-21. PMID:38126516. |
the geobia classification accuracy was assessed by performing a statistical analysis of confusion matrix: (2008): global accuracy = 0.92, kappa index = 0.84 and tau index = 0.84; and (2016): global accuracy = 0.93, kappa index = 0.86 and tau index = 0.86. |
2023-12-21 |
2023-12-23 |
Not clear |
| Edmund O Benefo, Shraddha Karanth, Abani K Pradha. A machine learning approach to identifying Salmonella stress response genes in isolates from poultry processing. Food research international (Ottawa, Ont.). vol 175. 2023-12-21. PMID:38128977. |
six machine learning algorithms (random forest, neural network, cost-sensitive learning, logit boost, and support vector machine linear and radial kernels) were trained on salmonella wgs data, and model fit was assessed using standard evaluation metrics such as the area under the receiver operating characteristic (auroc) curve and confusion matrix statistics. |
2023-12-21 |
2023-12-24 |
chicken |
| Rajul Mahto, Saboor Uddin Ahmed, Rizwan Ur Rahman, Rabia Musheer Aziz, Priyanka Roy, Saurav Mallik, Aimin Li, Mohd Asif Sha. A novel and innovative cancer classification framework through a consecutive utilization of hybrid feature selection. BMC bioinformatics. vol 24. issue 1. 2023-12-15. PMID:38102551. |
eight different benchmark microarray gene expression datasets of cancer have been utilized to analyze the performance of the proposed approach with different evaluation matrix such as recall, precision, f1-score, and confusion matrix. |
2023-12-15 |
2023-12-18 |
monkey |
| Nikolaos Haliasos, Matthew Pediaditis, Dimitrios Giakoumettis, Cleanthe Spanaki, Antonis Vakis, Vangelis Sakkali. Predicting impact of Deep Brain Stimulation on Non-motor symptoms of Parkinson's disease. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2023. 2023-12-12. PMID:38082785. |
the confusion matrix of the rf classifier gave a tpr of 0.92 and a fpr of 0.03. |
2023-12-12 |
2023-12-17 |
Not clear |
| Seng Hansun, Ahmadreza Argha, Hamid Alinejad-Rokny, Siaw-Teng Liaw, Branko G Celler, Guy B Mark. Revisiting Transfer Learning Method for Tuberculosis Diagnosis. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2023. 2023-12-12. PMID:38083096. |
several metrics derived from confusion matrix results were used, namely the accuracy (acc), sensitivity (sns), specificity (spc), precision (prc), and f1-score. |
2023-12-12 |
2023-12-17 |
Not clear |
| K Suresh Kumar Patro, Vinod Kumar Yadav, Vidya S Bharti, Arun Sharma, Arpita Sharma, T Senthilkuma. IoT and ML approach for ornamental fish behaviour analysis. Scientific reports. vol 13. issue 1. 2023-12-04. PMID:38049427. |
to compare the performance between all four classifiers, cross validation and confusion matrix used. |
2023-12-04 |
2023-12-10 |
Not clear |
| Deepanshu Parashar, Ashwani Kumar, Sarita Palni, Arvind Pandey, Anjaney Singh, Ajit Pratap Sing. Use of machine learning-based classification algorithms in the monitoring of Land Use and Land Cover practices in a hilly terrain. Environmental monitoring and assessment. vol 196. issue 1. 2023-12-04. PMID:38049547. |
the accuracy assessment was done using the confusion matrix based on the output results. |
2023-12-04 |
2023-12-10 |
Not clear |
| Yunyi Zhao, Haiming Luo, Jianan Chen, Rui Loureiro, Shufan Yang, Hubin Zha. Learning based motion artifacts processing in fNIRS: a mini review. Frontiers in neuroscience. vol 17. 2023-11-30. PMID:38033535. |
noting the absence of standard evaluation metrics for quality assessment of ma correction, we suggest a novel framework, integrating signal and model quality considerations and employing metrics like Δsignal-to-noise ratio (Δsnr), confusion matrix, and mean squared error. |
2023-11-30 |
2023-12-10 |
human |
| Geoff Phillips, Heliana Teixeira, Martyn Kelly, Fuensanta Salas Herrero, Gábor Várbíró, Anne Lyche Solheim, Agnieszka Kolada, Gary Free, Sandra Poikan. Setting nutrient boundaries to protect aquatic communities: The importance of comparing observed and predicted classifications using measures derived from a confusion matrix. The Science of the total environment. 2023-11-28. PMID:38013099. |
setting nutrient boundaries to protect aquatic communities: the importance of comparing observed and predicted classifications using measures derived from a confusion matrix. |
2023-11-28 |
2023-11-29 |
Not clear |