CME Velocity Field Calculation Model Based on an Unsupervised Transformer Optical Flow Network by Qingyang Chen, Hong Lin, Zhenping Qiang, Hui Liu, Kaifan Ji, Zhenhong Shang

“…Our model may be affected by overfitting during cross–data set inference, so we encourage performing a small amount of transfer learning on new data sets to mitigate this issue. …”
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Advanced Applications of Artificial Intelligence in Pharmacovigilance: Current Trends and Future Perspectives by Yogesh S Ahire, Jayesh H Patil, Harshita N Chordiya, Rashmi A Deore, Vinod A Bairagi

“…They are adept at applying sophisticated algorithms, machine learning models, and natural language processing to glean insights from unstructured data sources like clinical notes, patient narratives, and regulatory reports. …”
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Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis by Liping Tang, Dong Pang, Chengbang Wang, Jiali Lin, Shaohua Chen, Jiangchun Wu, Junqi Cui

“…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …”
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Use of Artificial Intelligence in Imaging Dementia by Manal Aljuhani, Azhaar Ashraf, Paul Edison

“…Clinical neuroimaging is amenable to errors owing to varying human judgement as the imaging data are complex and multidimensional. Artificial intelligence algorithms (machine learning and deep learning) enable automation of neuroimaging interpretation and may reduce potential bias and ameliorate clinical decision-making. …”
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Hydrogen Leakage Location Prediction in a Fuel Cell System of Skid-Mounted Hydrogen Refueling Stations by Leiqi Zhang, Qiliang Wu, Min Liu, Hao Chen, Dianji Wang, Xuefang Li, Qingxin Ba

“…The results show that the algorithm can predict leakage locations not included in the training set. …”
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Research on the evaluation method of cooperative jamming effectiveness based on IPSO-ELM by A. Tianjian Yang, B. Xing Wang, C. Siyi Cheng, D. You Chen, E. Xi Zhang

“…On this basis, the cooperative jamming decision schemes and their corresponding cooperative jamming effectiveness values are solved at different locations in the target space, and the results are detected as outliers using box plots, thus constructing sample data for cooperative jamming effectiveness evaluation. …”
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Penerapan Teknik Random Oversampling Untuk Memprediksi Ketepatan Waktu Lulus Menggunakan Algoritma Random Forest by Sri Diantika, Hiya Nalatissifa, Nurlaelatul Maulidah, Riki Supriyadi, Ahmad Fauzi

“…This research on the prediction of student graduation timeliness uses a random forest algorithm model. The data used in this research object has an unbalanced number of data classes, to overcome this, a random oversampling (ROS) resampling technique is applied and also applies Split validation or division between learning data by 50% for test data and 50%. …”
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Sparse Deep Neural Network for Encoding and Decoding the Structural Connectome by Satya P. Singh, Sukrit Gupta, Jagath C. Rajapakse

“…Brain state classification by applying deep learning techniques on neuroimaging data has become a recent topic of research. …”
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Aerial image segmentation of embankment dams based on multispectral remote sensing: a case study in the Belo Monte Hydroelectric Complex, Pará, Brazil by Carlos André de Mattos Teixeira, Thabatta Moreira Alves de Araujo, Evelin Cardoso, Marcos Antonio Costantin Filho, João Weyl Costa, Carlos Renato Lisboa Frances

“…Recently, multispectral remote sensing data and machine learning techniques have been applied to develop methodologies that enable automatic vegetation analysis and anomaly detection based on computer vision. …”
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Reversible Spectral Speech Watermarking with Variable Embedding Locations Against Spectrum-Based Attacks by Xuping Huang, Akinori Ito

“…Due to the integrity of the original data with probative importance, the algorithm requires reversibility, imperceptibility, and reliability. …”
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Will Artificial Intelligence Replace Physicians or Augment Their Capabilities? by Sara Rahmati Roodsari, Alireza Zali, Mohammad Rahmati-Roodsari, Behina Forouzanmehr

“…In dermatology, AI systems, and deep learning algorithms in particular, have reached levels of comparable accuracy to that of dermatologists in the detection of skin malignancies and inflammatory conditions, highlighting their potential as useful clinical decision-support tools11. …”
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The moderating role of professional grief in the relationship between job stress dimensions and turnover intention among nurses by Xue Liang, Jue Wang

“…XGBoost, known for enhancing sensitivity in detection and improving generalization performance, is particularly beneficial for high-dimensional problems and data heterogeneity. …”
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Automated analysis of vessel morphometry in retinal images from a Danish high street optician setting. by Josefine Freiberg, Roshan A Welikala, Jens Rovelt, Christopher G Owen, Alicja R Rudnicka, Miriam Kolko, Sarah A Barman, FOREVER consortium

“…<h4>Method</h4>The dataset FOREVERP (Finding Ophthalmic Risk and Evaluating the Value of Eye exams and their predictive Reliability, Pilot) contains retinal images obtained from a Danish high street optician chain. The QUARTZ algorithm utilizes both image processing and machine learning methods to determine retinal image quality, vessel segmentation, vessel width, vessel classification (arterioles or venules), and optic disc localization. …”
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A UAV Image Stitching Method for Complex Urban Environments by W. Niu, D. Qiu, R. Wu, R. Wu, Z. Wang, Y. Shi

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Transverse cracking in glass fibre-reinforced composites monitored with synchrotron X-ray multi-projection imaging by Elise Van Vlierberghe, Jeroen Soete, Eleni Myrto Asimakopoulou, Zisheng Yao, Julia Rogalinski, Zhe Hu, Kannara Mom, Bratislav Lukić, Christian Breite, Pablo Villanueava Perez, Yentl Swolfs

“…With these tools, a comparison between different lay-ups revealed that external transverse plies are much weaker than internal ones. An extensive data set was gathered to make a 3D reconstruction of the crack evolution over time using XMPI and machine learning-based reconstruction algorithms.  …”
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SmoothDectector: A Smoothed Dirichlet Multimodal Approach for Combating Fake News on Social Media by Akinlolu Oluwabusayo Ojo, Fatma Najar, Nuha Zamzami, Hanen T. Himdi, Nizar Bouguila

“…Although recent studies have explored multimodal fake news detection to learn shared representations of textual and visual information, they often learn discrete latent representations, merely concatenations of multimodal features. …”
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Molecular biomarkers in salivary diagnostic materials: Point-of-Care solutions — PoC-Diagnostics and -Testing by Ziyad S. Haidar

“…AI-driven algorithms now process and analyze salivary proteomic data with remarkable accuracy, identifying patterns and biomarkers associated with diseases such as oral cancer at an early stage. …”
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The Applications of Artificial Intelligence and Digital Twin in Power Systems: An In-Depth Review by Ghazal Rahmani-Sane, Sasan Azad, Mohammad Taghi Ameli, Sasan Haghani

“…This paper stands as the first comprehensive review of various AI techniques in power systems, spanning applications such as load forecasting, security assessment, voltage stability assessment, load shedding (LS), false data injection attack (FDIA) detection, state estimation and localization, fault detection and location, and power quality disturbances (PQDs) detection. …”
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Increasing use of artificial intelligence in genomic medicine for cancer care- the promise and potential pitfalls by Olivia O’Connor, Terri P. McVeigh

“…Artificial intelligence thrives on data, processing and learning from datasets with a degree of accuracy and efficiency that traditional computing algorithms can not achieve. …”
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Advancements in the application of artificial intelligence in the field of colorectal cancer by Mengying Zhu, Mengying Zhu, Zhenzhu Zhai, Yue Wang, Fang Chen, Ruibin Liu, Ruibin Liu, Xiaoquan Yang, Guohua Zhao

“…AI, utilizing machine learning (ML) and deep learning (DL) algorithms, improves early detection, diagnosis, and treatment by processing large volumes of medical data, uncovering hidden patterns, and forecasting disease development. …”
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