Machine learning in CTEPH: predicting the efficacy of BPA based on clinical and echocardiographic features by Qiumeng Xi, Juanni Gong, Jianfeng Wang, Xiaojuan Guo, Yuanhua Yang, Xiuzhang lv, Suqiao Yang, Yidan Li

“…The cohort was temporally split into a training set (2017–2021) and a test set (2022–2024). …”
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Development and validation of a multidimensional predictive model for 28-day mortality in ICU patients with bloodstream infections: a cohort study by Jun Jin, Jun Jin, Lei Yu, Qingshan Zhou, Qian Du, Xiangrong Nie, Hai-Yan Yin, Wan-Jie Gu

“…The model’s performance was evaluated using AUROC, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).ResultsThe nomogram demonstrated superior discrimination (AUROC: 0.760 vs. 0.671, P<0.001 for SOFA; 0.760 vs. 0.705, P<0.001 for APSIII; 0.760 vs. 0.707, P<0.001 for SAPS II) in the training cohort, with consistent performance in the validation cohort (AUROC: 0.742). …”
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Identifying mating events of group-housed broiler breeders via bio-inspired deep learning models by Venkat U.C. Bodempudi, Guoming Li, J. Hunter Mason, Jeanna L. Wilson, Tianming Liu, Khaled M. Rasheed

“…With custom training, the best performance of detecting broiler breeders via YOLOv8l was over 0.939 precision, recall, mAP50, mAP95, and F1 score for training and 0.95 positive and negative predicted values for testing. …”
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Estimating Chlorophyll-<i>a</i> and Phycocyanin Concentrations in Inland Temperate Lakes across New York State Using Sentinel-2 Images: Application of Google Earth Engine for Effic... by Sara Akbarnejad Nesheli, Lindi J. Quackenbush, Lewis McCaffrey

“…Expanding the temporal match using a one-day time window increased the available training dataset size and improved the fit of the linear regression model (R² of 0.71), highlighting the positive impact of increasing the training dataset on model fit. …”
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Global progress in competitive co-evolution: a systematic comparison of alternative methods by Stefano Nolfi, Paolo Pagliuca

“…The selected algorithms promote genuine progress by creating an archive of opponents used to evaluate evolving individuals, generating archives that include high-performing and well-differentiated opponents, identifying and discarding variations that lead to local progress only (i.e., progress against the opponents experienced and retrogressing against others). …”
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Prediction of Moisture Content in Kiwi (Actinidia deliciosa) Dried Using Machine Learning Approaches by Halil Nusret BULUS, Soner CELEN

“…Prediction models were developed using experimental data. The input for the training algorithm included kiwi slice thickness and drying time, while the output was the moisture content of the product. …”
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Optimization Strategies in Quantum Machine Learning: A Performance Analysis by Nouf Ali AL Ajmi, Muhammad Shoaib

“…This study presents a comprehensive comparison of multiple optimization algorithms applied to a quantum classification model, utilizing the Cleveland dataset. …”
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Automated Detection of Tailing Impoundments in Multi-Sensor High-Resolution Satellite Images Through Advanced Deep Learning Architectures by Lin Qin, Wenyue Song

“…While remote sensing enables large-scale monitoring, conventional methods relying on single-sensor data and traditional machine learning-based algorithm suffer from reduced accuracy in cluttered environments. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…Then, the most predictive radiomic features were selected and their corresponding coefficients were evaluated using the correlation coefficient algorithm and the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. …”
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Latent environment allocation of microbial community data. by Koichi Higashi, Shinya Suzuki, Shin Kurosawa, Hiroshi Mori, Ken Kurokawa

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On-line Diagnosis Technology for the Shock Absorbers on Subway Vehicle Based on RLS by WANG Yu, LYU Yu, ZHAO Muhua

“…To ensure the safety of train operation and avoid excessive maintenance of shock absorbers, based on the vibration data, a process parameter evaluation model of the recursive least squares (RLS) and a input-output model were presented according to the research of the metro vehicle on-line monitoring technology. …”
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The Interplay Between Loss Functions and Structural Constraints in Dependency Parsing by Robin Kurtz, Marco Kuhlmann

“…Our experimental evaluation shows that the modified loss function can yield improved parsing accuracy, compared to the unmodified baseline. …”
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Prediction of lymph node metastasis in papillary thyroid carcinoma using non-contrast CT-based radiomics and deep learning with thyroid lobe segmentation: A dual-center study by Hao Wang, Xuan Wang, Yusheng Du, You Wang, Zhuojie Bai, Di Wu, Wuliang Tang, Hanling Zeng, Jing Tao, Jian He

“…The combined model demonstrated superior diagnostic performance with AUCs of 0.830 (training), 0.799 (validation), 0.819 (temporal test), and 0.756 (external test), outperforming the DLRad model (AUCs: 0.786, 0.730, 0.753, 0.642), clinical model (AUCs: 0.723, 0.745, 0.671, 0.660), and radiologist evaluations (AUCs: 0.529, 0.606, 0.620, 0.503). …”
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Improving Word Embedding Using Variational Dropout by Zainab Albujasim, Diana Inkpen, Xuejun Han, Yuhong Guo

“…In recent years, many post-processing algorithms have been proposed to improve the pre-trained word embeddings. …”
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Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting by Farideh Sobhanifard

“…Providing flexible frameworks for the Neural Network training algorithm is one of the topics that has focused on many issues of the real world. …”
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A COMPARISON OF RANDOM FOREST AND DOUBLE RANDOM FOREST: DROPOUT RATES OF MADRASAH STUDENTS IN INDONESIA by Arie Purwanto, Bagus Sartono, Khairil Anwar Notodiputro

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Anomaly Detection in IoMT Environment Based on Machine Learning: An Overview by Peyman Vafadoost Sabzevar, Hamidreza Rokhsati, Alireza Chamansara, Ahmad Hajipour

“…In this article, the isolation forest algorithm was used for training on 80% of the dataset related to the data of the Internet of Medical Things network, and then this model was tested and evaluated on the remaining 20%. …”
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Consumer Happiness in the Purchase of Electric Vehicles: a Fuzzy Logic Model by Fernando Lámbarry-Vilchis, Aboud Barsekh Onji, Leticia Refugio Chavarría López, Paola Judith Maldonado Colín

“…This research was conducted using a fuzzy Delphi method survey targeting a specific consumer group and two fuzzy inference systems: a multi-input single-output FIS model and an FIS Tree employing a hierarchical fuzzy inference structure, which leverages the survey's training data to optimize the models using different machine learning algorithms. …”
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Lessons from the PROTECT-CH COVID-19 platform trial in care homes by Philip M Bath, Jonathan Ball, Matthew Boyd, Heather Gage, Matthew Glover, Maureen Godfrey, Bruce Guthrie, Jonathan Hewitt, Robert Howard, Thomas Jaki, Edmund Juszczak, Daniel Lasserson, Paul Leighton, Val Leyland, Wei Shen Lim, Pip Logan, Garry Meakin, Alan Montgomery, Reuben Ogollah, Peter Passmore, Philip Quinlan, Caroline Rick, Simon Royal, Susan D Shenkin, Clare Upton, Adam L Gordon

“…Results We initiated the trial including protocol, approvals, insurance, website, database, data algorithms, intervention selection and training materials. …”
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A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer by Sushant Patkar, Stephanie Harmon, Isabell Sesterhenn, Rosina Lis, Maria Merino, Denise Young, G. Thomas Brown, Kimberly M. Greenfield, John D. McGeeney, Sally Elsamanoudi, Shyh-Han Tan, Cara Schafer, Jiji Jiang, Gyorgy Petrovics, Albert Dobi, Francisco J. Rentas, Peter A. Pinto, Gregory T. Chesnut, Peter Choyke, Baris Turkbey, Joel T. Moncur

“…Training and validation of algorithms for cancer detection and grading were completed with three large datasets containing a total of 580 whole-mount prostate slides from 191 RP patients at two centers and 6218 annotated needle biopsy slides from the publicly available Prostate Cancer Grading Assessment dataset. …”
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