Envisioning Archival Images with Artificial Intelligence by Jessica Bushey

“…CV algorithms, such as object detection and image classification, can automate tasks like image metadata generation, offering archivists new tools for organizing collections more efficiently. …”
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A Literature Review on Arabic Automatic Question Generation by Abdulkhaleq Amin Abdullah, Khaled A. Al-Soufi

“… This comprehensive literature review is dedicated to the field of Arabic Automatic Question Generation (AQG), which focuses on the development of computational models and algorithms for the automatic generation of questions. …”
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piRNA in Machine-Learning-Based Diagnostics of Colorectal Cancer by Sienna Li, Valentina L. Kouznetsova, Santosh Kesari, Igor F. Tsigelny

“…To test the validity of our model, we used data from piRBase with known associations with CRC that we did not use to train the ML model. …”
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Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma by Yun Liang, Yun Liang, Min He, Wenqing Chen, Wenqing Chen, Lizhen Li, Lizhen Li, Yumeng Dong, Yumeng Dong, Gang Liang, Hui Huangfu, Zengyu Jiang, Zengyu Jiang, Sheng He, Sheng He, Sheng He

“…BackgroundLymph node metastases (LNM) in laryngeal squamous cell carcinoma (LSCC) has been associated with lower survival, but current imaging methods, such as computed tomography (CT), have limited capabilities to identify them. …”
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GREEN ECONOMY AND HOLISTIC PLANNING BY ARTIFICIAL INTELLIGENCEAPPLICATION by STEVOVIC IVAN, HADROVIĆ SABAHUDIN, JOVANOVIC MIHAILO

“…This manuscript provides a systematic overview of the advantages and drawbacks associated with AI deployment in green sectors. On the one hand, IT such as machine learning, data analytics, and optimization algorithms offer immense potential to enhance resource efficiency, optimize energy systems, and facilitate sustainable decision-making processes. …”
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Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment by Zhiling Wang, Xinquan Chen, Bin Liu, Jinjin Hai, Kai Qiao, Zhen Yuan, Lianjun Yang, Bin Yan, Zhihai Su, Hai Lu

“…<b>Objective:</b> This study aims to apply different deep learning convolutional neural network algorithms to assess the grading of cervical spinal stenosis and to evaluate their consistency with clinician grading results as well as clinical manifestations of patients. …”
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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

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OPTIMIZATION OF TEACHING METHODS IN SPORTS CLASSES WITH STUDENTS WITH VISUAL IMPAIRMENTS by Mariana Albert, Evald Albert

“…The motivation for conducting the present research is the creation of kinesitherapeutic algorithms adapted to visually impaired student so that they can achieve greater autonomy and activity in motor skills during sports classes. …”
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Automated machine learning for predicting perioperative ischemia stroke in endovascularly treated ruptured intracranial aneurysm patients by Yuhang Peng, Ke Bi, Xiaolin Zhang, Ning Huang, Xiang Ji, Weifu Chen, Ying Ma, Yuan Cheng, Yongxiang Jiang, Jianhe Yue

“…The least absolute shrinkage and selection operator (LASSO) method was used to screen essential features associated with PIS. Based on these features, nine machine learning models were constructed using a training set (75% of participants) and assessed on a test set (25% of participants). …”
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Surface Quality Monitoring and Improvement for Dimensional Metrology in Inline CT by Denoising with Neural Networks and Fast Surface Quality Metric by Faizan Ahmad, Ahmed Baraka, César Cardona-Marin, Steffen Kieß, Dominik Wolfschläger, Robert H. Schmitt, Sven Simon

“…To address this challenge, denoising methods based on neural networks have been used, outperforming traditional algorithms such as BM3D. In this work, we investigate the Noise2Noise method, which trains a neural network using pairs of noisy images, eliminating the need for clean ground truth data—typically unavailable in CT. …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…The final classification algorithm achieved classification metrics with high accuracy (99%). …”
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Fractional-Order Controller for the Course Tracking of Underactuated Surface Vessels Based on Dynamic Neural Fuzzy Model by Guangyu Li, Yanxin Li, Xiang Li, Mutong Liu, Xuesong Zhang, Hua Jin

“…Aiming at the uncertainty problem caused by the time-varying modeling parameters associated with ship speed in the course tracking control of underactuated surface vessels (USVs), this paper proposes a control algorithm based on the dynamic neural fuzzy model (DNFM). …”
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Predictive value of the stone-free rate after percutaneous nephrolithotomy based on multiple machine learning models by Zhao Rong Liu, Zhao Rong Liu, Zhan Jiang Yu, Jie Zhou, Jian Biao Huang

“…The patients were randomly divided into a training set and a test set in a 7:3 ratio. Clinical data were collected, and univariate analysis was performed to identify important data significantly associated with the stone-free rate after PCNL. …”
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Identification of a 10-species microbial signature of inflammatory bowel disease by machine learning and external validation by Shicheng Yu, Jun Li, Zhaofeng Ye, Mengxian Zhang, Xiaohua Guo, Xu Wang, Liansheng Liu, Yalong Wang, Xin Zhou, Wei Fu, Michael Q. Zhang, Ye-Guang Chen

“…The model's performance significantly improved when trained on high-quality data from the Chinese population. …”
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Robust object counting through distribution uncertainty matching and optimal transport by Sabri Boughorbel, Fethi Jarray, Rachida Zegour, Nauman Ullah Gilal, Khaled Al Thelaya, Marco Agus, Jens Schneider

“…Although such labeling is cost-effective, trained models can be sensitive to annotation noise. …”
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Improvements in Image Registration, Segmentation, and Artifact Removal in ThermOcular Imaging System by Navid Shahsavari, Ehsan Zare Bidaki, Alexander Wong, Paul J. Murphy

“…A novel addition to the system includes the use of EyeTags, which assist clinicians in selecting control points more easily, thus reducing errors associated with manual selection. Furthermore, the integration of state-of-the-art semantic segmentation models trained on the newest dataset is explored. …”
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Detection of Damage on Inner and Outer Races of Ball Bearings Using a Low-Cost Monitoring System and Deep Convolution Neural Networks by Handeul You, Dongyeon Kim, Juchan Kim, Keunu Park, Sangjin Maeng

“…With recent rapid advancements in machine learning algorithms, there is increasing interest in proactively diagnosing bearing faults by analyzing signals obtained from bearings. …”
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Exploring the relationship between dietary patterns and health-related quality of life among Iranian adult population: Tehran lipid and glucose study by Mahdieh Niknam, Somayeh Hosseinpour-Niazi, Sara Jalali-Farahani, Parisa Amiri, Parvin Mirmiran, Firoozeh Hosseini-Esfahani, Elaheh Ainy, Fereidoun Azizi

“…Abstract Background The current study aims to investigate the association between dietary patterns and health-related quality of life (HRQoL) in a large Iranian adult population. …”
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Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment by L. M. Sheridan, D. Duplyakin, C. Phillips, H. Tinnesand, H. Tinnesand, R. K. Rai, J. E. Flaherty, L. K. Berg

“…The risk associated with poor correlation between the observed and reference datasets decreases with increasing training period length. …”
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Development and validation of a machine learning-based predictive model for compassion fatigue in Chinese nursing interns: a cross-sectional study utilizing latent profile analysis by Lijuan Yi, Ting Shuai, Jingjing Zhou, Liang Cheng, Maria F. Jiménez-Herrera, Xu Tian

“…Eight machine learning algorithms were applied to predict compassion fatigue, with performance assessed through cross-validation, calibration, and discrimination metrics. …”
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