All Relations between Confusion and matrix compartment

Publication Sentence Publish Date Extraction Date Species
Zhengyang Lan, Mathieu Lempereur, Gwenael Gueret, Laetitia Houx, Marine Cacioppo, Christelle Pons, Johanne Mensah, Olivier Rémy-Néris, Abdeldjalil Aïssa-El-Bey, François Rousseau, Sylvain Brochar. Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning. Computers in biology and medicine. vol 171. 2024-02-13. PMID:38350399. we evaluated the accuracy, sensitivity, specificity, f1 score, area under the curve (auc) score, and confusion matrix of the predictions by resnet, lstm, and inceptiontime deep learning architectures for time series data. 2024-02-13 2024-02-16 human
Luelue Huang, Miaoling Liu, Bin Li, Bimal Chitrakar, Xu Dua. Terahertz Spectroscopic Identification of Roast Degree and Variety of Coffee Beans. Foods (Basel, Switzerland). vol 13. issue 3. 2024-02-10. PMID:38338523. the classification effect and misclassification of the model were analyzed via confusion matrix. 2024-02-10 2024-02-12 Not clear
Yu-Jen Fang, Chien-Wei Huang, Riya Karmakar, Arvind Mukundan, Yu-Ming Tsao, Kai-Yao Yang, Hsiang-Chen Wan. Assessment of Narrow-Band Imaging Algorithm for Video Capsule Endoscopy Based on Decorrelated Color Space for Esophageal Cancer: Part II, Detection and Classification of Esophageal Cancer. Cancers. vol 16. issue 3. 2024-02-10. PMID:38339322. the evaluation of the model's performance was based on the produced confusion matrix and five key metrics: precision, recall, specificity, accuracy, and f1-score of the trained model. 2024-02-10 2024-02-12 Not clear
Chitrabhanu B Gupta, Debraj Basu, Timothy K Williams, Lucas P Neff, Michael A Johnson, Nathan T Patel, Aravindh S Ganapathy, Magan R Lane, Fatemeh Radaei, Chen-Nee Chuah, Jason Y Adam. Improving the precision of shock resuscitation by predicting fluid responsiveness with machine learning and arterial blood pressure waveform data. Scientific reports. vol 14. issue 1. 2024-01-26. PMID:38278825. model performance was assessed using the area under the receiver operating characteristic curve (auroc), confusion matrix metrics, and calibration curves plotting predicted probabilities against observed outcomes. 2024-01-26 2024-01-29 Not clear
Angela Lii, Jonathan Temte, Shari Barlow, Maureen Goss, Emily Temte, Jen Zaborek, Amra Uzicani. Assessment and comparison of the ILI case definition in clinical and school-based community settings: ORCHARDS/IISP. Annals of family medicine. vol 21. issue Suppl 3. 2024-01-25. PMID:38271207. relationships between influenza and each categorical variable were described by the confusion matrix, sensitivity, and specificity. 2024-01-25 2024-01-28 human
Erum Yousef Abbasi, Zhongliang Deng, Arif Hussain Magsi, Qasim Ali, Kamlesh Kumar, Asma Zubed. Optimizing Skin Cancer Survival Prediction with Ensemble Techniques. Bioengineering (Basel, Switzerland). vol 11. issue 1. 2024-01-22. PMID:38247920. the performance was evaluated and interpreted using accuracy, precision, recall, f1 score, confusion matrix, and roc curves, where the voting method achieved a promising accuracy of 99%. 2024-01-22 2024-01-24 Not clear
Xiyuan Liu, Liying Wang, Hongyan Yan, Qingjiao Cao, Luyao Zhang, Weiguo Zha. Optimizing the Probabilistic Neural Network Model with the Improved Manta Ray Foraging Optimization Algorithm to Identify Pressure Fluctuation Signal Features. Biomimetics (Basel, Switzerland). vol 9. issue 1. 2024-01-22. PMID:38248606. the evaluation indicators include confusion matrix, accuracy, precision, recall rate, f1-score, and accuracy and error rate. 2024-01-22 2024-01-24 Not clear
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