A novel brain tumor magnetic resonance imaging dataset (Gazi Brains 2020): initial benchmark results and comprehensive analysis by Seref Sagiroglu, Ramazan Terzi, Emrah Celtikci, Alp Özgün Börcek, Yilmaz Atay, Bilgehan Arslan, Mustafa Caglar Sahin, Kerem Nernekli, Umut Demirezen, Okan Bilge Ozdemir, Kevser Özdem Karaca, Nuh Azgınoğlu

“…Furthermore, the dataset is analyzed using eight different deep learning models for high-grade glioma tumor prediction, classification, and detection tasks. Additionally, this study demonstrates the results of an explainable Artificial Intelligence (XAI) approach applied to the trained models. …”
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Apple Watercore Grade Classification Method Based on ConvNeXt and Visible/Near-Infrared Spectroscopy by Chunlin Zhao, Zhipeng Yin, Yushuo Tan, Wenbin Zhang, Panpan Guo, Yaxing Ma, Haijian Wu, Ding Hu, Quan Lu

“…These images served as input for training and prediction using the ConvNeXt deep convolutional neural network. …”
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New opportunities and trends in international investment driven by machine learning by Li Chang, Cai Linxin, Lin Qinni, Huang Yujie

“…Finally, it is proved that the application performance of the improved mean variance model based on random forest revenue prediction is higher.…”
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A new numerical method for processing longitudinal data: clinical applications by Ilaria Stura, Emma Perracchione, Giuseppe Migliaretti, Franco Cavallo

“…Results: Here, we propose an alternative approach to be used as effective and accurate tool for the parameters fitting and prediction of individual trajectories from sparse longitudinal data. …”
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Hybridising Neurofuzzy Model the Seasonal Autoregressive Models for Electricity Price Forecasting on Germany’s Spot Market by Dorel Mihai Paraschiv, Narciz Bălășoiu, Souhir Ben-Amor, Raul Cristian

“…Despite the growing interest in predictive algorithms, the challenges are difficult to overcome given the restricted access to relevant data series and the lack of accurate metrics. …”
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Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…This work assists researchers in selecting the most effective bio-inspired algorithm for disease categorization, prediction, and the analysis of high-dimensional biomedical data.…”
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Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses by Yuan Sun, Yan Li, Anlan Zhang, Tao Hu, Ming Li

“…The research underscores the critical role of ribosome biogenesis in the progression and treatment resistance of pancreatic cancer, offering valuable new perspectives for prognostic evaluation and therapeutic response prediction in pancreatic cancer.…”
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Inversion of SPAD Values of Pear Leaves at Different Growth Stages Based on Machine Learning and Sentinel-2 Remote Sensing Data by Ning Yan, Qu Xie, Yasen Qin, Qi Wang, Sumin Lv, Xuedong Zhang, Xu Li

“…This study establishes a robust SPAD retrieval framework that integrates multi-source features and multiple models, enhancing prediction accuracy across different growth stages and providing technical support for intelligent orchard monitoring and precision management.…”
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Legal Analysis of AI-Generated Creations: Copyright Law Perspectives by Praja Chrisna Bagus Edhita, Hakim Hary Abdul, Basri, Kurniaty Yulia, Sari Elvira Purnama

“…Legal analysis shows that AI is just a computer programming tool that performs tasks based on human commands. AI uses algorithms and computer training for recognition, prediction, and decision-making. …”
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Vital node searcher: find out critical node measure with deep reinforcement learning by Guanting Du, Fei Zhu, Quan Liu

“…Moreover, a duelling Q network module is developed to enhance the precision of prediction. Both in terms of time complexity and performance, the VNS method is superior compared with other methods, which are validated by experiments of real world datasets. …”
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Uncertainty of industrial noise measurement at distant locations from the source by Tadeusz Wszołek

“…The paper deals with some real word data of partial uncertainties of noise prediction and measurement from large industry and impulse sound sources, taken in different meteorological conditions. …”
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An Improved Kernelized Correlation Filter for Extracting Traffic Flow in Satellite Videos by Dudu Guo, Hongbo Shuai, Jie Zhang, Yang Wang, Miao Sun

“…Second, we utilized the Kalman filter for trajectory prediction to reduce the loss of target during vehicle tracking. …”
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Enhancing Visual–Inertial Odometry Robustness and Accuracy in Challenging Environments by Alessandro Minervini, Adrian Carrio, Giorgio Guglieri

“…Visual–Inertial Odometry (VIO) algorithms are widely adopted for autonomous drone navigation in GNSS-denied environments. …”
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On the effect of sampling frequency on the electricity theft detection performance by Fatemeh Soleimani Nasab, Foad Ghaderi

“…Recently, machine and deep learning techniques are being used widely to detect thieves by analysing the consumption patterns. While the prediction accuracy of these methods depends on the number and quality of the existing samples used for training models, the majority of previous research work focussed on data with high sampling frequencies, for example, data from smart grids. …”
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Vehicle Detection and Shape Refinement Based on LiDAR by YU An, HU Dongfang, WANG Xuepeng, ZHANG Jin, ZHOU Yan, XIE Guotao, QIN Xiaohui, HU Manjiang

“…Accurate vehicle detection and shape estimation can provide accurate static information for follow-up tracking and prediction. Although the existing vehicle detection algorithm based on lidar can accurately detect and classify each target vehicle, there is a problem of unstable estimation when the vehicle point cloud contour is partially obscured in an "L" shape. …”
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Artificial intelligence-driven metabolic engineering is applied to the development of active ingredients in Traditional Chinese Medicine by Zhang Guoqi, Wang Juan

“…In this paper, we introduce AI-driven machine learning algorithms in prediction models, and also review recent research progress on AI-assisted metabolic engineering design and production of high-value compounds, focusing on how to use AI methods to achieve directed evolution of strains.…”
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AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

“…By leveraging state-of-the-art convolutional neural networks (CNNs) like GoogLeNet, AlexNet, and ResNet18, alongside traditional classifiers such as k-nearest neighbors (KNN) and support vector machine (SVM), we ensure robust prediction capabilities. Our preprocessing methods significantly improve input data quality, leading to promising detection accuracies. …”
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Hybrid Laminar Flow Control Optimizations for Infinite Swept Wings by Yayun Shi, Xiayu Lan, Tihao Yang

“…The Reynolds-averaged Navier-Stokes (RANS) solver coupled with the linear stability theory is applied for the laminar-turbulent transition prediction, and the traditional optimization method based on evolutionary algorithms is applied for laminar flow wing optimization. …”
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Exploration of shared pathogenic factors and causative genes in early-stage endometrial cancer and osteoarthritis by Yiyun Bai, Sang Luo, Ruzhen Shuai, Xiaomei Zhang, Liwei Yuan, Dan Liu

“…Genes with diagnostic value were identified using multiple machine learning algorithms to construct EC prediction models and evaluate their performance. …”
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The Growing Impact of Natural Language Processing in Healthcare and Public Health by Aadit Jerfy, Owen Selden, Rajesh Balkrishnan PhD

“…Automating labor intensive and tedious tasks with language processing algorithms, using text analytics systems and machine learning to analyze social media data and extracting insights from unstructured data allows for better public sentiment analysis, enhancement of risk prediction models, improved patient communication, and informed treatment decisions. …”
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