Capturing the songs of mice with an improved detection and classification method for ultrasonic vocalizations (BootSnap). by Reyhaneh Abbasi, Peter Balazs, Maria Adelaide Marconi, Doris Nicolakis, Sarah M Zala, Dustin J Penn

“…This study aims to 1) determine the most efficient USV detection tool among the existing methods, and 2) develop a classification model that is more generalizable than existing methods. …”
Get full text

Exploring Score-Level and Decision-Level Fusion of Inertial and Video Data for Intake Gesture Detection by Hamid Heydarian, Marc T. P. Adam, Tracy L. Burrows, Megan E. Rollo

“…We first assess the potential of fusion by contrasting the performance of the individual models in intake gesture detection. The assessment shows that fusing the outputs of individual models is more promising on the OREBA-DIS dataset. …”
Get full text

Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis with Crimean-Congo Hemorrhagic Fever Data by Osman Demir, Ünal Erkorkmaz

“…Outlier(s) are identified with the help of residuals, Bootstrap Hypothesis test and Rank product test.Method: In R.4.0.3 software, outlier(s) are determined on a clinical dataset by the Schoenfeld residual, Martingale residual, Deviance residual method and Bootstrap Hypothesis test (BHT) based on Concordance index, and Rank product test.Results: After the cox regression established by the backward stepwise and robust cox regression, it was observed that the established models did not fit. …”
Get full text

Circulating MicroRNAs as Non-Invasive Biomarkers for Early Detection of Non-Small-Cell Lung Cancer. by Magdalena B Wozniak, Ghislaine Scelo, David C Muller, Anush Mukeria, David Zaridze, Paul Brennan

“…Internal validation of model discrimination was conducted by calculating the bootstrap optimism-corrected AUC for the selected model.…”
Get full text

Early and accurate nutrient deficiency detection in hydroponic crops using ensemble machine learning and hyperspectral imaging by Nagarajan S․, Maria Merin Antony, Murukeshan Vadakke Matham

“…In this context, this research presents and proposes different machine learning-based approaches that utilizes ensemble techniques such as Random Forest (RF), Bagging or Bootstrap Aggregating, Adaboost or Adaptive Boosting, and eXtreme Gradient Boosting (XGB) classifiers for early detection of nutrient deficiencies in hydroponic crops. …”
Get full text

Study on Title Encoding Methods for e-Commerce Downstream Tasks by Cristian Cardellino, Rafael Carrascosa

“…We also propose an adaptation of a deep network architecture from the Computer Vision field: ``Bootstrap Your Own Latent'' (BYOL), to learn product embeddings based on the title and compare it to several industrial baselines as well as some state-of-the-art supervised models. …”
Get full text

Analyzing Taiwanese Traffic Patterns on Consecutive Holidays Through Forecast Reconciliation and Prediction-Based Anomaly Detection Techniques by Mahsa Ashouri, Frederick Kin Hing Phoa, Marzia Angela Cremona

“…We propose a prediction-based detection method for identifying highway traffic anomalies using reconciled ordinary least squares (OLS) forecasts and bootstrap prediction intervals. …”
Get full text

Protocol for detecting neuronal subnetworks from in vivo calcium imaging data using multiple clustering algorithms in MATLAB by Jui-Yen Huang, Gautam Chauhan, Pei-Ying Chen, Esen Tuna, Hui-Chen Lu

“…We apply statistical modeling in R to evaluate group-level differences, followed by model selection and bootstrapping for robust estimation. …”
Get full text

Normal serum protein electrophoresis and mutated IGHV genes detect very slowly evolving chronic lymphocytic leukemia patients by Jasmine Chauzeix, Marie‐Pierre Laforêt, Mélanie Deveza, Liam Crowther, Elodie Marcellaud, Paco Derouault, Anne‐Sophie Lia, François Boyer, Nicolas Bargues, Guillaume Olombel, Arnaud Jaccard, Jean Feuillard, Nathalie Gachard, David Rizzo

Get full text

Modelling the Transmission Dynamics of Tuberculosis in the Ashanti Region of Ghana by Felix Okoe Mettle, Prince Osei Affi, Clement Twumasi

“…Mathematical models can aid in elucidating the spread of infectious disease dynamics within a given population over time. …”
Get full text

Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection. by Islam Zada, Esraa Omran, Salman Jan, Hessa Alfraihi, Seetah Alsalamah, Abdullah Alshahrani, Shaukat Hayat, Nguyen Phi

“…The dynamical growth of cyber threats in IoT setting requires smart and scalable intrusion detection systems. In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”
Get full text

Psychological distress in biliary tract malignancy patients: influencing factors and development of a predictive nomogram model by Zhennan Gou, Yuhua Liu, Wenjie Tang, Changming Zhou, Zhenqi Lu, Lu Wang, Wei Feng, Weiqi Xu, Jun Wang

“…The R software was employed to create a nomogram model, and the model’s accuracy and predictive performance were assessed using the receiver operating characteristic curve (ROC) and the Hosmer-Lemeshow test.ResultsThe average score of psychological distress among the 219 patients was (3.91 ± 2.44), with a psychological distress detection rate of 54.8%. …”
Get full text

Early identification of mild cognitive impairment: an innovative model using ocular biomarkers by Lingjing Zhang, Lingjing Zhang, Yanwei Wang, Yuming Liu, Zi Ye, Zhaohui Li

“…Internal validation was performed using 1,000-resample bootstrap analysis, while model calibration was assessed through calibration curves and Brier scores. …”
Get full text

Predicting Remaining Useful Life Based on Hilbert–Huang Entropy with Degradation Model by Yuhuang Zheng

“…In the training phase, the degradation detection threshold and the failure threshold of this model are estimated by the distribution of 600 bootstrapped samples. …”
Get full text

Hybrid feature fusion in cervical cancer cytology: a novel dual-module approach framework for lesion detection and classification using radiomics, deep learning, and reproducibilit... by Shurong Niu, Lili Zhang, Lina Wang, Xue Zhang, Erniao Liu

“…Four deep learning models, Swin Transformer, YOLOv11, Faster R-CNN, and DETR (DEtection TRansformer), were employed for lesion detection, and their performance was compared using mAP, IoU, precision, recall, and F1-score. …”
Get full text

Modeling Estuarine Algal Bloom Dynamics with Satellite Data and Spectral Index-Based Classification by Mayya Podsosonnaya, Maria J. Schreider, Sergei Schreider

“…The logistic regression model was trained for each pixel; then the optimal parameters for its coefficients and the optimal classification threshold were obtained by cross-validation based on bootstrapping. …”
Get full text

Development and validation of a risk prediction model for acute kidney injury in coronary artery disease by Ming Ye, Chang Liu, Duo Yang, Hai Gao

“…This study focuses on developing accurate predictive models to improve the early detection and prognosis of AKI in CAD patients. …”
Get full text

Clinical-genomic characteristics of homologous recombination deficiency (HRD) in breast cancer: application model for practice by Jinsui Du, Lizhe Zhu, Chenglong Duan, Nan Ma, Yudong Zhou, Danni Li, Jianing Zhang, Jiaqi Zhang, Yalong Wang, Xi Liu, Yu Ren, Bin Wang

“…The area under the ROC curve (AUC) of the combined prediction model combining HER2 status and Ki- 67 index was 0.749, and the accuracy of the model was further validated using bootstrap resampling (500 replicates), resulting in an AUC of 0.730, indicating a high predictive accuracy for HRD status. …”
Get full text

A CGM-Based model for predicting hypoglycemia in type 2 diabetes patients with TIR in target by Jianwen Lu, Danrui Chen, Beisi Lin, Zhigu Liu, Yanling Yang, Ling He, Jinhua Yan, Daizhi Yang, Wen Xu

“…Data were bootstrapped 1000 times for internal validation, and a calibration curve was drawn to evaluate the model’s predictive ability. …”
Get full text

Using easy-to-collect indices to develop and validate models for identifying metabolic syndrome and pre-metabolic syndrome by Chao Shi, Chao Shi, Yin Cheng, Ling Ma, Lanqiqi Wu, Hongjuan Shi, Yining Liu, Yining Liu, Jinyu Ma, Jinyu Ma, Huitian Tong, Huitian Tong

“…These same models were subsequently applied to pre-MetS detection as a secondary analysis. …”
Get full text