Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis by Ali Nabavi, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Farimah Safari

“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
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Open-Set Recognition of Environmental Sound Based on KDE-GAN and Attractor–Reciprocal Point Learning by Jiakuan Wu, Nan Wang, Huajie Hong, Wei Wang, Kunsheng Xing, Yujie Jiang

“…While open-set recognition algorithms have been extensively explored in computer vision, their application to environmental sound analysis remains understudied. …”
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YouTube and Bilibili as sources of information on oral cancer: cross-sectional content analysis study by Qilei zhang, Zhe Li, Huiping Zhang, Ling Han, Shugang Zhao, Siyu Jia

“…In order to promote high-quality health information, it is essential to encourage the development of more professional content creators and to optimize platform algorithms.…”
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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. …”
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The effect of implementing parenteral nutrition guideline on growth and clinical outcomes in preterm infants: a comparative study by Majid Mahallei, Lida Gorbani, Mohammad Bagher Hoseini, Elnaz Shaseb, Bahareh Mehramuz, Khatereh Rezazadeh

“…The PRE group received individualized PN formulations based on clinician discretion, while the POST group received PN guided by a newly introduced, stepwise algorithmic protocol aiming to optimize early protein and energy intake. …”
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About designing a planned education system in an existing corporate infrastructure by D. T. Gedenidze, A. V. Sinitsyn

“…Despite the availability of solutions for corporate training on the market, developing your own system is still the optimal solution for a large company, allowing you to satisfy all the needs of employees and managers in managing corporate training, as well as the most optimal way to integrate the system into the existing over many years, the company’s technological infrastructure, while avoiding the involvement of thirdparty specialists.…”
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Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

“…IoT-connected bins transmit data to a central server, which uses blockchain to ensure secure, transparent data storage. AI algorithms, including machine learning (ML) and deep learning (DL), classify waste in real-time, optimizing waste collection and recycling. …”
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Group twirling and noise tailoring for multiqubit controlled phase gates by Guoding Liu, Ziyi Xie, Zitai Xu, Xiongfeng Ma

“…Specifically, for multiqubit controlled phase gates, which are essential in quantum algorithms and directly implementable in practice, we determine optimal twirling groups within the realm of classically replaceable unitary operations. …”
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Contrast-enhanced ultrasound radiomics model for predicting axillary lymph node metastasis and prognosis in breast cancer: a multicenter study by Shi Yu Li, Yue Ming Li, Yong Qi Fang, Zhi Ying Jin, Jun Kang Li, Xiao Meng Zou, Si Si Huang, Rui Lan Niu, Nai Qing Fu, Yu Hong Shao, Xuan Tong Gong, Mao Ran Li, Wei Wang, Zhi Li Wang

“…LASSO regression was employed to select radiomic features (RFs), while eight machine learning algorithms were utilized to construct radiomic models based on US, CDFI, and CEUS. …”
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Biobjective Scheduling for Joint Parallel Machines with Sequence-Dependent Setup by Taking Pareto-Based Approach by Wichai Srisuruk, Kanchala Sudtachat, Paramate Horkaew

“…The resultant manufacturing plans obtained by these algorithms are thoroughly assessed and discussed.…”
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A Review of Enhancement Techniques for Cone Beam Computed Tomography Images by Hassn Mazin Al-alaaf, Mohammed Sabah Jarjees

“…These methods encompass various mathematical algorithms, machine learning approaches, and hybrid models, which aim to mitigate the imperfections present in CBCT data while preserving diagnostically relevant information. …”
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Efficient Context-Preserving Encoding and Decoding of Compositional Structures Using Sparse Binary Representations by Roman Malits, Avi Mendelson

“…In addition, the proposed algorithms allow to optimize the amount of compute and memory needed to achieve the desired encoding/decoding performance.…”
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Artificial intelligence for smart irrigation: Reducing water consumption and improving agricultural output by Arlanova A. A., Hojamkuliyeva B. A., Babanazarov N. Sh., Arlanov M. S.

“…A mathematical model based on machine learning algorithms is developed to predict the optimal water volume required for irrigation of agricultural crops. …”
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Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach by Mar Roca, Chengfa Benjamin Lee, Avi Putri Pertiwi, Alina Blume, Isabel Caballero, Gabriel Navarro, Dimosthenis Traganos

“…We developed a satellite-based workflow to complement in situ seagrass monitoring efforts in the Balearic Islands (Western Mediterranean), reducing field expenses while covering regional spatial scales. Our synoptic tool uses Sentinel-2 A/B satellite imagery at 10 m spatial resolution to generate a multi-temporal composite (2016–2022) of the Balearic Islands’ coastal waters within the Google Earth Engine cloud computing platform, optimizing image processing and highlighting the importance of a high-resolution bathymetric dataset to increase seagrass mapping accuracies. …”
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Design, Fabrication, and Application of Large-Area Flexible Pressure and Strain Sensor Arrays: A Review by Xikuan Zhang, Jin Chai, Yongfu Zhan, Danfeng Cui, Xin Wang, Libo Gao

“…Real-time data processing requires innovative solutions such as edge computing and machine learning algorithms, ensuring low-latency, high-accuracy data interpretation while preserving the flexibility of sensor arrays. …”
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Intelligent collaborative management and control platform for continuous mining equipment in open-pit mines by Zhiyong LEI, Xiaolong MA, Shujun ZHAO, Shiming ZHANG, Bin YAN

“…The platform integrates advanced technologies, including dual-ring network transmission, network security protocols, multi-machine cooperative control, digital twin modeling, and big data analytics, facilitating effective coordination among coal miners, transfer machines, unloaders, and conveyors for seamless continuous mining operations.Three critical technical challenges are addressed: ① The implementation of dual-ring network transmission technology reduces data transmission latency and enhances network stability. ② A secure network transmission framework has been developed to safeguard data confidentiality and integrity. ③ The multi-machine cooperative control system incorporates data acquisition, process control, and 3D visualization modules, employing real-time monitoring and optimized control algorithms to boost mining and transportation efficiency while ensuring the continuity of multi-machine operations. …”
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Hemorrhage risk associated with triple antithrombotic therapy: a focused real-world pharmacovigilance disproportional analysis study by Kannan Sridharan, Gowri Sivaramakrishnan

“…Conclusion This study highlights the elevated hemorrhage risk associated with TAT, particularly with rivaroxaban, while apixaban appears safer in terms of bleeding and mortality. …”
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New Challenging Systemic Therapies for Juvenile Scleroderma: A Comprehensive Review by Chiara Sassetti, Claudia Borrelli, Martha Mazuy, Cristina Guerriero, Donato Rigante, Susanna Esposito

“…Large, multicenter, long-term trials are urgently needed to establish safety, efficacy, and optimal treatment algorithms that are tailored to the pediatric population.…”
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Applicability Evaluation of Provincial Precipitation Real-time Analysis Product in Beijing by Zhao Wenfang, Wang Huiying, Meng Huifang, Miao Yupeng, Huang Mingming, Fan Min, Tang Wei

“…The intensity of light rain exceeds the observation, while the spatial distribution difference of bias is evident. …”
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Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN by Yousuf Babiker M. Osman, Wei Li

“…Moreover, stochastic gradient descent (SGD) is used to train each layer of SAE to optimize weight parameters, while a strategy of genetic algorithms to identify the number of neurons in each hidden layer is developed. …”
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