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  1. 241

    Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda by Sandra Ruth Babirye, Mike Nsubuga, Gerald Mboowa, Charles Batte, Ronald Galiwango, David Patrick Kateete

    Published 2024-12-01
    “…This study aimed to explore the potential of machine learning algorithms in predicting drug resistance of four anti-TB drugs (rifampicin, isoniazid, streptomycin, and ethambutol) in MTB using whole-genome sequence and clinical data from Uganda. …”
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  2. 242
  3. 243

    Fault Diagnosis System of Induction Motors Based on Neural Network and Genetic Algorithm Using Stator Current Signals by Tian Han, Bo-Suk Yang, Won-Ho Choi, Jae-Sik Kim

    Published 2006-01-01
    “…This paper proposes an online fault diagnosis system for induction motors through the combination of discrete wavelet transform (DWT), feature extraction, genetic algorithm (GA), and neural network (ANN) techniques. …”
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  4. 244
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    Prediction of pathological grade of oral squamous cell carcinoma and construction of prognostic model based on deep learning algorithm by Tingru Shao, Peirong Ni, Chun Wang, Jiahui Li, Xiaozhi Lv

    Published 2025-06-01
    “…The deep learning model constructed by CLAM algorithm achieved an AUC of 0.86 in the training set and an AUC of 0.71 in the external validation set. …”
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  6. 246
  7. 247

    Optimal Design Method of a Hybrid CSP-PV Plant Based on Genetic Algorithm Considering the Operation Strategy by Rongrong Zhai, Ying Chen, Hongtao Liu, Hao Wu, Yongping Yang

    Published 2018-01-01
    “…When the system is optimized by the operation characteristics of the whole year, the lowest LCOE is 0.0555 $/kWh, the rated capacity of PV and CSP system are 242.954 MW and 30 MW, respectively, and the capacity of heat storage and battery are 136.059 MWh and 8.977 MWh. …”
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    Estimating Nurse Workload Using a Predictive Model From Routine Hospital Data: Algorithm Development and Validation by Paul Meredith, Christina Saville, Chiara Dall’Ora, Tom Weeks, Sue Wierzbicki, Peter Griffiths

    Published 2025-07-01
    “…ObjectiveThe objective of this study is to explore whether an algorithm could estimate ward workload using existing routinely recorded data. …”
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  10. 250

    Research on coal mine robot positioning algorithm based on integration of ORB-SLAM3 vision and inertial navigation by Wei CHEN, Shuaida WU, Zijian TIAN, Fan ZHANG, Yi LIU

    Published 2025-06-01
    “…According to the principle of tight coupling of visual inertial navigation, the residual function of the whole positioning system is constructed by fusing visual residual error and IMU residual error, and the sliding window BA algorithm based on nonlinear optimization is used to iteratively optimize the residual function to obtain accurate pose estimation of the mobile robot. …”
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  11. 251

    Seasonal forecasting of the hourly electricity demand applying machine and deep learning algorithms impact analysis of different factors by Heba-Allah Ibrahim El-Azab, R. A. Swief, Noha H. El-Amary, H. K. Temraz

    Published 2025-03-01
    “…Precision improvements are also considered when creating a model. Where the whole database is split into four seasons based on demand patterns. …”
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  12. 252
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    Performance Comparison of 10 State-of-the-Art Machine Learning Algorithms for Outcome Prediction Modeling of Radiation-Induced Toxicity by Ramon M. Salazar, PhD, Saurabh S. Nair, MS, Alexandra O. Leone, MBS, Ting Xu, PhD, Raymond P. Mumme, BS, Jack D. Duryea, BA, Brian De, MD, Kelsey L. Corrigan, MD, Michael K. Rooney, MD, Matthew S. Ning, MD, Prajnan Das, MD, Emma B. Holliday, MD, Zhongxing Liao, MD, Laurence E. Court, PhD, Joshua S. Niedzielski, PhD

    Published 2025-02-01
    “…Purpose: To evaluate the efficacy of prominent machine learning algorithms in predicting normal tissue complication probability using clinical data obtained from 2 distinct disease sites and to create a software tool that facilitates the automatic determination of the optimal algorithm to model any given labeled data set. …”
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  14. 254
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    Multi-Layer Perceptron Neural Network Utilizing Adaptive Best-Mass Gravitational Search Algorithm to Classify Sonar Dataset by Mohammad Reza MOSAVI, Mohammad KHISHE, Mohammad Jafar NASERI, Gholam Reza PARVIZI, Mehdi AYAT

    Published 2019-01-01
    “…To lift defections, this study uses Adaptive Best Mass Gravitational Search Algorithm (ABGSA) to train MLP NN. This algorithm develops marginal disadvantage of the GSA using the best-collected masses within iterations and expediting exploitation phase. …”
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  16. 256
  17. 257

    Vehicle Text Data Compression and Transmission Method Based on Maximum Entropy Neural Network and Optimized Huffman Encoding Algorithms by Jingfeng Yang, Zhenkun Zhang, Nanfeng Zhang, Ming Li, Yanwei Zheng, Li Wang, Yong Li, Ji Yang, Yifei Xiang, Yu Zhang

    Published 2019-01-01
    “…In order to optimize the efficiency of mass data transmission in actual operation, this paper presented the text information (including position information) of the maximum entropy principle of a neural network probability prediction model combined with the optimized Huffman encoding algorithm, optimization from the exchange of data to data compression, transmission, and decompression of the whole process. …”
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  18. 258

    An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid by Yanming Cheng, Jinqi Zhang, Mahmoud Al Shurafa, Dejun Liu, Yulian Zhao, Chao Ding, Jing Niu

    Published 2025-05-01
    “…The prediction system is implemented by using 8760 samples based on an hourly meteorological data of a whole year. GA is used as an optimization technique for training MANFIS to accomplish the desired objects of EMS. …”
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  19. 259

    Analysis of Regions of Homozygosity: Revisited Through New Bioinformatic Approaches by Susana Valente, Mariana Ribeiro, Jennifer Schnur, Filipe Alves, Nuno Moniz, Dominik Seelow, João Parente Freixo, Paulo Filipe Silva, Jorge Oliveira

    Published 2024-12-01
    “…Homozygosity mapping (HM) leverages ROHs to identify genes associated with autosomal recessive diseases. Whole-exome sequencing (WES) improves HM by detecting ROHs and disease-causing variants. …”
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  20. 260

    Generating Training Data for Deep Learning-Based Segmentation Algorithms by Projecting Existing Labels onto Additional Aerial Images by F. Kurz, N. Merkle, C. Henry, R. Bahmanyar, F. Rauch, J. Hellekes, V. Gstaiger, D. Rosenbaum, P. Reinartz

    Published 2025-05-01
    “…Highly accurate manually-generated labels in aerial and satellite images are used for the training of deep learning-based segmentation algorithms and should be available in large numbers and cover many different scenarios to increase the accuracy and generalization capability of the underlying models. …”
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