Artificial intelligence as a diagnostic aid in cross-sectional radiological imaging of the abdominopelvic cavity: a protocol for a systematic review by Natalie S Blencowe, Neil J Smart, George E Fowler, Rhiannon C Macefield, Conor Hardacre, Mark P Callaway

“…This may improve the performance of diagnostic, prognostic and management decisions. …”
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Machine learning for predicting all-cause mortality of metabolic dysfunction-associated fatty liver disease: a longitudinal study based on NHANES by Xueni Wang, Huihui Chen, Luqiao Wang, Wenguang Sun

“…This study aimed to develop different machine learning models to predict all-cause mortality of MAFLD individuals, compare the predictive performance of these models, and identify the risk factors contributing all-cause mortality, which is crucial for management of MAFLD individuals. …”
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Advancements in digital twin technology and machine learning for energy systems: A comprehensive review of applications in smart grids, renewable energy, and electric vehicle optim... by Opy Das, Muhammad Hamza Zafar, Filippo Sanfilippo, Souman Rudra, Mohan Lal Kolhe

“…DT concepts facilitate the creation of virtual models mirroring physical assets, streamlining real-time data management and analysis. …”
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Integrating cyber-physical systems with embedding technology for controlling autonomous vehicle driving by Manal Abdullah Alohali, Hamed Alqahtani, Abdulbasit Darem, Monir Abdullah, Yunyoung Nam, Mohamed Abouhawwash

“…To address these constraints, this study incorporates double deep Q networks (DDQN) to improve the agent’s adaptability under uncertain driving conditions. …”
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Research Progress and Applications of Artificial Intelligence in Agricultural Equipment by Yong Zhu, Shida Zhang, Shengnan Tang, Qiang Gao

“…The findings reveal a deep integration of AI models with multimodal perception technologies, significantly improving the operational efficiency, resource utilization, and environmental adaptability of agricultural equipment. …”
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The role of artificial intelligence in occupational health in radiation exposure: a scoping review of the literature by Zohreh Fazli, Mehran Sadeghi, Mohebat Vali, Parvin Ahmadinejad

“…Abstract Introduction Artificial intelligence (AI) has the potential to significantly enhance workplace safety and mitigate occupational radiation exposure risks by improving the accuracy of assessment and management of these hazards. …”
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Enhancing dosimetric precision in the treatment of cancerous tumors: Gamma Index validation and Monte Carlo simulations of 6 and 12 megavoltage photon beams from Varian Medical lin... by Ali H. D. Alshehri

“…These findings underscore the potential of MC simulations to improve the accuracy and reliability of radiotherapy treatment plans. …”
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An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…The MHA module effectively models global spatial-task dependencies among nodes, enhancing solution quality. …”
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Advancing Grid-Forming Inverter Technology: Comprehensive PQ Capability and Performance Analysis by Md Nurunnabi, Shuhui Li, Himadry Shekhar Das

“…Recognizing that IBR operational constraints are distinct from those of synchronous generators, this study develops advanced PQ capability models and algorithmic frameworks that accurately characterize GFM inverter operational constraints across various coupling filter configurations (L, LC, and LCL). …”
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Enhanced Underwater Image Restoration and Clarity Optimization Using Advanced Digital Image Processing Techniques by Gopirajan Punniyakotti Varadharajan, Pradeep T., Charan R.

“…Furthermore, Gaussian bilateral filtering and Rayleigh stretching are utilized as denoising methods and edge clarity improvement. From the outcomes of the experiment based on PSNR and SSIM metrics, it is evident that the method presented in this paper has better performance than the traditional algorithms. …”
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Advancing Alzheimer's Therapy: Computational strategies and treatment innovations by Jibon Kumar Paul, Abbeha Malik, Mahir Azmal, Tooba Gulzar, Muhammad Talal Rahim Afghan, Omar Faruk Talukder, Samar Shahzadi, Ajit Ghosh

“…Moreover, machine learning algorithms enhance early diagnosis and enable precision medicine strategies by analyzing multi-modal datasets. …”
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Challenges of the Biopharmaceutical Industry in the Application of Prescriptive Maintenance in the Industry 4.0 Context: A Comprehensive Literature Review by Johnderson Nogueira de Carvalho, Felipe Rodrigues da Silva, Erick Giovani Sperandio Nascimento

“…The limitations presented in the literature include a reduced number of models, the lack of a clearer understanding of its construction, lack of applications directly linked to the biopharmaceutical industry, and lack of measurement of costs and implementation time of these models. …”
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A Survey on Video Compression Optimization Techniques for Accuracy Enhancement in Video Analytics Applications (VAPs) by Kholidiyah Masykuroh, Hendrawan, Eueung Mulyana, Farhan Krishna

“…We examine traditional compression algorithms, machine learning-based approaches, dynamic parameter adjustment strategies, and hybrid models, each offering unique strengths and limitations. …”
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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…Among these, the most common problem is the lack of broader and consistent datasets, followed by the need for existing models for further improvement.…”
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Neurotechnological Approaches to Cognitive Rehabilitation in Mild Cognitive Impairment: A Systematic Review of Neuromodulation, EEG, Virtual Reality, and Emerging AI Applications by Evgenia Gkintoni, Stephanos P. Vassilopoulos, Georgios Nikolaou, Apostolos Vantarakis

“…Emerging AI applications showed potential for personalized assessment and intervention through predictive modeling and adaptive algorithms. <i>Conclusions:</i> Neurotechnological approaches offer promising avenues for MCI rehabilitation, with the most substantial evidence for integrated interventions targeting multiple mechanisms. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…By integrating machine learning (ML) algorithms, such as Gradient Boosting Models and Support Vector Machines, with SHAP-based feature visualization, robust screening methods were applied to ensure the reliability of predictions. …”
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Intelligent Interior Design Systems: Optimizing Layouts and Aesthetics Using AI and User Data by Zhe Ji, Yan Yu

“…Optimization algorithms, including hybrid evolutionary strategies, are guided by learned aesthetic and functionality scores to efficiently explore the solution space. …”
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Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples. by Fatma Alamri, Imad Barsoum, Shrinivas Bojanampati, Maher Maalouf

“…These models are evaluated based on the coefficient of determination and the mean squared error. …”
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Recurrent neural networks for aerodynamic parameter estimation with Lyapunov stability analysis by Sara Mohan George, S. S. Selvi, J. R. Raol

“…The RNN-Gradient shows a 20% performance improvement over RNN-WB. Satisfactory simulation results from both algorithms provide a promising foundation for their potential applications to real flight test data.…”
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Trend equation prediction in medical and pharmaceutical studies (the example of respiratory diseases development in children in the region) by O. V. Zhukova, S. V. Kononova, T. M. Konyshkina

“…However, mathematical models and computational algorithms for monitoring, predicting incidence, spread and prevention of various nosologies are still to be developed.…”
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