| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| 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 |
| 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. |
for this purpose, the examination of the proportions of matching and mismatching status classifications of nutrients and a biological quality element using a confusion matrix is a key step that should be more widely adopted in threshold selection. |
2023-11-28 |
2023-11-29 |
Not clear |
| Chunling Wang, Cuicui Mia. Study on the Prediction Model of Wound Infection After Spinal Fusion and Internal Fixation Based on Logistic Regression. Studies in health technology and informatics. vol 308. 2023-11-26. PMID:38007797. |
in this paper, logistic logistic regression, smote algorithm and confusion matrix are used to model the probability of infection after spinal fusion and internal fixation. |
2023-11-26 |
2023-11-28 |
Not clear |
| Raghav V Anand, Abdul Quadir Md, Shabana Urooj, Senthilkumar Mohan, Mohamad A Alawad, Adittya . Enhancing Diagnostic Decision-Making: Ensemble Learning Techniques for Reliable Stress Level Classification. Diagnostics (Basel, Switzerland). vol 13. issue 22. 2023-11-25. PMID:37998591. |
to assess the model's performance, different metrics were used, such as the confusion matrix, accuracy, precision, recall, and f1 score. |
2023-11-25 |
2023-11-28 |
Not clear |
| Lloyd Prosper Chisedzi, Mbika Muteb. Detection of Broken Rotor Bars in Cage Induction Motors Using Machine Learning Methods. Sensors (Basel, Switzerland). vol 23. issue 22. 2023-11-25. PMID:38005467. |
a confusion matrix was used to validate the models' performance using accuracy, precision, recall, and f1-scores. |
2023-11-25 |
2023-11-28 |
Not clear |
| Zepeng Wang, Jianping Chen, Wei Chen, Changyuan Wan, Yunyan Liu, Junjie Huan. Susceptibility assessment of environmental geological disasters in Liulin County based on RF: from the perspective of positive and negative sample proportion. Environmental science and pollution research international. 2023-11-16. PMID:37968480. |
the results indicate that, through a confusion matrix test, the model's predictive performance reaches a "tipping point" at a sample ratio of 1:5. |
2023-11-16 |
2023-11-20 |
Not clear |
| Brij B Gupta, Kwok Tai Chui, Akshat Gaurav, Varsha Arya, Priyanka Chaurasi. A Novel Hybrid Convolutional Neural Network- and Gated Recurrent Unit-Based Paradigm for IoT Network Traffic Attack Detection in Smart Cities. Sensors (Basel, Switzerland). vol 23. issue 21. 2023-11-14. PMID:37960386. |
additionally, the confusion matrix offers valuable insights into the model's performance across these attack types. |
2023-11-14 |
2023-11-20 |
Not clear |
| Danjing Zhao, Linna Ji, Fengbao Yan. Land Cover Classification Based on Airborne Lidar Point Cloud with Possibility Method and Multi-Classifier. Sensors (Basel, Switzerland). vol 23. issue 21. 2023-11-14. PMID:37960542. |
finally, the confidence degree of each classifier for different categories was calculated by the confusion matrix and normalized to obtain the weights. |
2023-11-14 |
2023-11-20 |
Not clear |
| Qiong Wu, Jing Yu, Mingjin Zhang, Yinran Xiong, Lijia Zhu, Bo Wei, Ting Wu, Yiping D. Serum lipidomic profiling for liver cancer screening using surface-assisted laser desorption ionization MS and machine learning. Talanta. vol 268. issue Pt 2. 2023-11-06. PMID:37931569. |
the best diagnostic performance was attained by linear discriminant analysis (lda), which has a confusion matrix accuracy of 98.3 %. |
2023-11-06 |
2023-11-08 |
Not clear |
| Şuayip Burak Duman, Duygu Çelik Özen, Ibrahim Şevki Bayrakdar, Oğuzhan Baydar, Elham S Abu Alhaija, Dilek Helvacioğlu Yiğit, Özer Çelik, Rohan Jagtap, Roberta Pileggi, Kaan Orha. Second mesiobuccal canal segmentation with YOLOv5 architecture using cone beam computed tomography images. Odontology. 2023-11-01. PMID:37907818. |
confusion matrix and receiver-operating characteristic (roc) analysis were used in the statistical evaluation of the results. |
2023-11-01 |
2023-11-08 |
Not clear |