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    Genetic prediction of male pattern baldness. by Saskia P Hagenaars, W David Hill, Sarah E Harris, Stuart J Ritchie, Gail Davies, David C Liewald, Catharine R Gale, David J Porteous, Ian J Deary, Riccardo E Marioni

    Published 2017-02-01
    “…By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. …”
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  3. 2503

    Multi-objective-based economic dispatch and loss reduction in the presence of electric vehicles considering different optimization techniques by David Hmingthanmawia, Subhasish Deb, Subir Datta, Ksh. Robert Singh, Umit Cali, Umit Cali, Taha Selim Ustun

    Published 2024-10-01
    “…The multi-objective grasshopper optimization algorithm and the ant-lion optimization are compared to observe the minimum cost and total loss of the system. …”
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    Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

    Published 2025-05-01
    “…Particle Swarm Optimization, Grey Wolf Optimizer, Pendulum Search Algorithm, and Whale Optimization Algorithm were employed to reduce the feature space, removing approximately 45% of clinical and analytical variables while maintaining high recall for the minority class of patients experiencing hypotension. …”
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    Article
  6. 2506

    Synthetic graphs for link prediction benchmarking by Alexey Vlaskin, Eduardo G Altmann

    Published 2025-01-01
    “…Predicting missing links in complex networks requires algorithms that are able to explore statistical regularities in the existing data. …”
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    Mapping and interpretability of aftershock hazards using hybrid machine learning algorithms by Bo Liu, Haijia Wen, Mingrui Di, Junhao Huang, Mingyong Liao, Jingyuan Yu, Yutao Xiang

    Published 2025-08-01
    “…By employing the stacking algorithm to optimize and combine XGBoost and LightGBM models, the proposed model significantly improves the prediction performance. …”
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  9. 2509

    Conformational ensembles for protein structure prediction by Jiaan Yang, Wen Xiang Cheng, Peng Zhang, Gang Wu, Si Tong Sheng, Junjie Yang, Suwen Zhao, Qiyue Hu, Wenxin Ji, Qiong Shi

    Published 2025-03-01
    “…The P53_HUMAN as a well-known protein and LEF1_HUMAN and Q8GT36_SPIOL as typical disordered proteins are token as the benchmark to evaluate the predicted outcomes. The results demonstrated an effective algorithm and biological meaningful process well to predict protein multiple conformation structures.…”
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  10. 2510

    Leveraging the Louvain algorithm for enhanced group formation and collaboration in online learning environments by Minkyung Lee, Priya Sharma

    Published 2024-12-01
    “…The local analysis, focusing on the intricacies of node and edge connections, underscores that the Louvain algorithm's classifications correlate with heightened cohesiveness and collaborative potential. …”
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    Event Prediction Using Spatial–Temporal Data for a Predictive Traffic Accident Approach Through Categorical Logic by Eleftheria Koutsaki, George Vardakis, Nikos Papadakis

    Published 2025-06-01
    “…We also present a model for predicting traffic accidents using categorical logic, creating a Knowledge Base using the Resolution algorithm as a proof of concept. …”
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  13. 2513

    Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction. by Ruiyu Zhan

    Published 2025-01-01
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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  14. 2514

    An Integrated Algorithm with Feature Selection, Data Augmentation, and XGBoost for Ovarian Cancer by Jingxun Cai, Zne-Jung Lee, Zhihxian Lin, Chih-Hung Hsu, Yun Lin

    Published 2024-12-01
    “…First, we can simplify the original genetic dataset through feature selection methods, removing irrelevant variables and noise, thereby improving the model’s predictive accuracy. Following dimensionality reduction, AC-GAN enriches the data, producing more realistic genetic samples to enhance the model’s generalization capacity. …”
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  15. 2515

    A Novel Scheme for Improving Accuracy of KNN Classification Algorithm Based on the New Weighting Technique and Stepwise Feature Selection by Saeid Sheikhi, Mohammad Taghi Kheirabadi, Amin Bazzazi

    Published 2020-12-01
    “…Furthermore, this algorithm does not consider the differences between samples, which led the algorithm to have inaccurate predictions. …”
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  16. 2516

    Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images by Pingli Sun, Chenxia Wang, Min Li, Lanqi Liu

    Published 2021-01-01
    “…In this paper, we describe in detail the principles of the space-time noise reduction filter, propose a 3D-filter algorithm for Gaussian noise, an improved 3D-filter algorithm based on the 3D-BDP (bloom-deep-split) filter for mixed noise, and a filter algorithm for luminance and color noise in low-brightness scenes. …”
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  17. 2517

    A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression by Hilario Gómez-Moreno, Pedro Gil-Jiménez, Sergio Lafuente-Arroyo, Roberto López-Sastre, Saturnino Maldonado-Bascón

    Published 2014-01-01
    “…A modified median filter based on a previous noise detection stage and a regression-based filter are presented and compared to other well-known state-of-the-art noise reduction algorithms. The results show that the filters proposed achieved good results, outperforming other state-of-the-art algorithms for low and medium noise ratios, and were comparable for very highly corrupted images.…”
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  18. 2518

    How low can you go: evaluating electrode reduction methods for EEG-based speech imagery BCIs by Maurice Rekrut, Maurice Rekrut, Johannes Ihl, Tobias Jungbluth, Antonio Krüger, Antonio Krüger

    Published 2025-07-01
    “…In this study, we evaluated several electrode reduction algorithms in combination with various feature extraction and classification methods across three distinct EEG-based speech imagery datasets to identify the optimal number and position of electrodes for SI-BCIs. …”
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