Development and calibration of roundabout safety performance functions using machine learning: a case study from Amman, Jordan by Diana Al-Nabulsi, Aya Hassouneh

“…Comparative modeling was conducted using ordinary least squares regression and Random Forest Regressor algorithms. The linear regression model yielded an R 2 of 0.542 with a high sum of squared errors (SSE = 3750.38), underscoring its limited capacity to capture non-linear relationships. …”
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Ship Magnetic Signature Classification Using GRU-Based Recurrent Neural Networks by Kajetan Zielonacki, Jaroslaw Tarnawski, Miroslaw Woloszyn

“…Features, advantages and limitations of developed algorithms are derived strictly from the nature of neural networks.…”
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REDalign: accurate RNA structural alignment using residual encoder-decoder network by Chun-Chi Chen, Yi-Ming Chan, Hyundoo Jeong

“…REDalign significantly reduces computational complexity compared to Sankoff-style algorithms and effectively handles non-nested structures, including pseudoknots, which are challenging for traditional alignment methods. …”
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A Novel Three-Dimensional Direction-of-Arrival Estimation Approach Using a Deep Convolutional Neural Network by Constantinos M. Mylonakis, Zaharias D. Zaharis

“…This article aims to constitute a noteworthy contribution to the domain of direction-of-arrival (DoA) estimation through the application of deep learning algorithms. We approach the DoA estimation challenge as a binary classification task, employing a novel grid in the output layer and a deep convolutional neural network (DCNN) as the classifier. …”
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Analyzing the Impact of Geoenvironmental Factors on the Spatiotemporal Dynamics of Forest Cover via Random Forest by Hendaf N. Habeeb, Yaseen T. Mustafa

“…The Random Forest model demonstrated high predictive accuracy, achieving an R² value of 0.918 (RMSE of 0.016 and MAE of 0.013) for 2013 and 0.916 (RMSE of 0.018 and MAE of 0.014) for 2023, underscoring the model’s robustness in handling nonlinear ecological processes. …”
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Pharmacological potential of 3,5-dimethyl-4-(3-(5-nitrofuran-2-yl)allylidenamino)-1-alkyl-1,2,4-triazolium bromides by A. S. Hotsulia, O. I. Panasenko, T. S. Brytanova

“…A molecular docking method that uses a variety of computational algorithms to predict and analyze interactions, including determining the presence of possible binding sites, estimating binding energies, and the spatial arrangement of molecules. …”
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Single-cell and machine learning approaches uncover intrinsic immune-evasion genes in the prognosis of hepatocellular carcinoma by Jiani Wang, Xiaopeng Chen, Donghao Wu, Changchang Jia, Qinghai Lian, Yuhang Pan, Jiumei Yang

“…Time-dependent receiver operating characteristic analysis demonstrated the accurate predictive capability of the risk score model for HCC prognosis. …”
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Comparison of clinical nasal endoscopy, optical biopsy, and artificial intelligence in early diagnosis and treatment planning in laryngeal cancer: a prospective observational study by Ruifang Hu, Xianping Liu, Yong Zhang, Clement Arthur, Dongguang Qin

“…Diagnostic performance was calculated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).ResultsThe study revealed superior sensitivity (95.2%) and specificity (96.5%) with AI-enhanced endoscopy compared to conventional endoscopy (89.6%, 92.4%), respectively. …”
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Unveiling psychobiological correlates in primary Sjögren’s syndrome: a machine learning approach to determinants of disease burden by László V. Módis, László V. Módis, András Matuz, András Matuz, Zsófia Aradi, Ildikó Fanny Horváth, Antónia Szántó, Antal Bugán

“…Three machine learning algorithms were trained to predict outcome variables, first by each measure category, then on the entire set of predictor variables. …”
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Identification and validation of TUBB, CLTA, and FBXL5 as potential diagnostic markers of postmenopausal osteoporosis by Yue Tan, Yujing Wang, Qin Zhu, Yan Xue, Xuhao Ji, Zhenkun Li, Jiawen Shen, Chengming Sun, Shiqi Ren, Chenlin Zhang, Jianfeng Chen

“…Additionally, we intersected the clusters to identify differentially expressed genes (DEGs) and analyzed potential diagnostic markers for PMOP using support vector machine recursive feature elimination (SVM-RFE), LASSO, and random forest (RF) algorithms, which were subsequently validated in the GSE56116 dataset. …”
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Machine learning-driven multi-omics analysis identifies a prognostic gene signature associated with programmed cell death and metabolism in hepatocellular carcinoma by Xiang Li, Donghao Yin, Jiahao Geng, Yanyu Xu, Zijing Xu, Xuemeng Yang, Quanwei Li, Zimeng Shang, Zhiyun Yang, Zhong Xu, Jiabo Wang, Enxiang Zhang, Xinhua Song

“…Based on prognosis-related DEGs, patients and cells were stratified into high- and low-expression groups using corresponding computational algorithms. The intersecting DEGs from both datasets were analyzed using univariate Cox regression, and a prognostic risk score model was constructed through machine learning algorithms. …”
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Peripherex Home Visual Field Demonstrates High Test-Retest Reliability, Validity by Schweitzer J, Ibach M, Berdahl J, Daoud M, Daoud YA, Kempinski Y, Goldberg JL

“…Detection of abnormal fields was excellent, with a sensitivity of 95.7% and a negative predictive value (NPV) of 98.27%. Detection of normal fields was very good, with a specificity of 79.26% and a positive predictive value (PPV) of 66.36%. …”
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UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma by Haofeng Yin, Yibo Xue, Chen Wang, Yanqin Wu, Yuchen Guo, Chunzhen Li, Yunyan Zhang, Shulei Yin, Tiejun Zhao

“…The role of UBE2N in predicting tumor therapeutic susceptibility was characterized using bioinformatics algorithms combined with publicly available CRISPR screening datasets and immunotherapy cohorts. …”
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Identification and Validation of Key Genes Involved in the Coupling of Mitochondria-Associated Endoplasmic Reticulum Membrane in Hemorrhoidal Disease by Mao L, Rao Z, Wang Y, Yang J, He J, Zheng Z, Chen L

“…Additionally, CIBERSORT algorithms were utilized to evaluate immune cell infiltration abundance, differences, and correlations in the samples. …”
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A fully automated, expert-perceptive image quality assessment system for whole-body [18F]FDG PET/CT by Cong Zhang, Xin Gao, Xuebin Zheng, Jun Xie, Gang Feng, Yunchao Bao, Pengchen Gu, Chuan He, Ruimin Wang, Jiahe Tian

“…Automated identification and localization algorithms were applied to select predefined pairs of PET and CT slices from whole-body images. …”
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Remote sensing reveals the role of forage quality and quantity for summer habitat use in red deer by Thomas Rempfler, Christian Rossi, Jan Schweizer, Wibke Peters, Claudio Signer, Flurin Filli, Hannes Jenny, Klaus Hackländer, Sven Buchmann, Pia Anderwald

“…In particular, our approach employed random forest regression algorithms, integrating various remote sensing variables such as reflectance values, vegetation indices and optical traits derived from a radiative transfer model. …”
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Enhanced quantitation of pathological α-synuclein in patient biospecimens by RT-QuIC seed amplification assays. by Ankit Srivastava, Qinlu Wang, Christina D Orrù, Manel Fernandez, Yaroslau Compta, Bernardino Ghetti, Gianluigi Zanusso, Wen-Quan Zou, Byron Caughey, Catherine A A Beauchemin

“…This enhanced assay format discriminated as little as 2-fold differences in αSynD seed concentration besides detecting ~2-16-fold seed reductions caused by inactivation treatments. In some scenarios, analysis of the data using Poisson and midSIN algorithms provided more consistent and statistically significant discrimination of different seed concentrations. …”
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Using de novo assembly to identify structural variation of eight complex immune system gene regions. by Jia-Yuan Zhang, Hannah Roberts, David S C Flores, Antony J Cutler, Andrew C Brown, Justin P Whalley, Olga Mielczarek, David Buck, Helen Lockstone, Barbara Xella, Karen Oliver, Craig Corton, Emma Betteridge, Rachael Bashford-Rogers, Julian C Knight, John A Todd, Gavin Band

“…Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. …”
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Towards an Efficient Remote Sensing Image Compression Network with Visual State Space Model by Yongqiang Wang, Feng Liang, Shang Wang, Hang Chen, Qi Cao, Haisheng Fu, Zhenjiao Chen

“…Furthermore, in comparison to traditional codecs and learned image compression algorithms, our model achieves BD-rate reductions of −4.48%, −9.80% over the state-of-the-art VTM on the AID and NWPU VHR-10 datasets, respectively, as well as −6.73% and −7.93% on the panchromatic and multispectral images of the WorldView-3 remote sensing dataset.…”
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A public benchmark for human performance in the detection of focal cortical dysplasia by Lennart Walger, Matthias H. Schmitz, Tobias Bauer, David Kügler, Fabiane Schuch, Christophe Arendt, Tobias Baumgartner, Johannes Birkenheier, Valeri Borger, Christoph Endler, Franziska Grau, Christian Immanuel, Markus Kölle, Patrick Kupczyk, Asadeh Lakghomi, Sarah Mackert, Elisabeth Neuhaus, Julia Nordsiek, Anna‐Maria Odenthal, Karmele Olaciregui Dague, Laura Ostermann, Jan Pukropski, Attila Racz, Klaus von derRopp, Frederic Carsten Schmeel, Felix Schrader, Aileen Sitter, Alexander Unruh‐Pinheiro, Marilia Voigt, Martin Vychopen, Philip vonWedel, Randi vonWrede, Ulrike Attenberger, Hartmut Vatter, Alexandra Philipsen, Albert Becker, Martin Reuter, Elke Hattingen, Alexander Radbruch, Rainer Surges, Theodor Rüber

“…The benchmark test set was chosen to consist of 15 subjects most predictive for human performance and 13 subjects identified by at most 3 of the 28 readers. …”
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