RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…Considering that the ordinary non-maximum suppression method in dense occlusion scenarios will incorrectly suppress the prediction box of the occluded object, EIOU was used to optimize the non-maximum suppression method. …”
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Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke by Gianluca Brugnara, Michael Baumgartner, Edwin David Scholze, Katerina Deike-Hofmann, Klaus Kades, Jonas Scherer, Stefan Denner, Hagen Meredig, Aditya Rastogi, Mustafa Ahmed Mahmutoglu, Christian Ulfert, Ulf Neuberger, Silvia Schönenberger, Kai Schlamp, Zeynep Bendella, Thomas Pinetz, Carsten Schmeel, Wolfgang Wick, Peter A. Ringleb, Ralf Floca, Markus Möhlenbruch, Alexander Radbruch, Martin Bendszus, Klaus Maier-Hein, Philipp Vollmuth

“…Pseudo-prospective external validation was performed in consecutive patients with suspected AIS from 4 different hospitals during a 6-month timeframe and demonstrated high sensitivity (≥87%) and negative predictive value (≥93%). Benchmarking against two CE- and FDA-approved software solutions showed significantly higher performance for our ANN with improvements of 25–45% for sensitivity and 4–11% for NPV (p ≤ 0.003 each). …”
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Current status and prospects of artificial intelligence in the diagnosis and treatment of bladder tumors by GAN Xiya, WEI Wei

“…Machine learning and deep learning algorithms have played an important role in the imaging detection and diagnosis of bladder tumors, providing high accuracy in tumor detection, grading, and staging predictions. …”
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The Use of Artificial Intelligence in Medical Diagnostics: Opportunities, Prospects and Risks by Nataliia Sheliemina

“…However, the AI use in medicine carries certain risks related to ethics and data privacy, shortcomings in the quality of data for training algorithms, and importance of protecting against cyberthreats. …”
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A New Approach to Characterize Superplastic Materials from Free-Forming Test and Inverse Analysis by Gillo Giuliano, Wilma Polini

“…In fact, the maximum percentage error, regarding the prediction of the forming times of a free-forming process, was reduced from 20% to 8%. …”
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CLINICAL AND LABORATORY ASPECTS OF DETECTING SPECIFIC IgE ANTIBODIES TO COW’S MILK AND ITS COMPONENTS by N. A. Alkhutova, N. A. Kovyazina, O. L. Zhizhina

“…An immunochemoluminescent assay of specific IgE antibody levels to the cow milk using IMMULITE 2000/XPi analyzer has revealed its good informative value at different approaches to prediction and evaluation of food allergy treatment, both oriented for a critical cutoff value of 3 МU/L, and by monitoring a decrease in antibody levels. …”
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Current Status of Application of Spaceborne GNSS-R Raw Intermediate-Frequency Signal Measurements: Comprehensive Review by Qiulan Wang, Jinwei Bu, Yutong Wang, Donglan Huang, Hui Yang, Xiaoqing Zuo

“…These research results have important application potential in fields such as environmental monitoring, climate change research, and weather prediction, and are expected to provide new technological means for global geophysical parameter retrieval.…”
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Harnessing Artificial Intelligence and Innovative Vaccines for Mpox Diagnosis and Control: A Comprehensive Narrative Review by Excel Onajite Ernest-Okonofua, Zainab Abdullahi Zubairu, Malik Olatunde Oduoye, Maryam Tariq, Syed Muhammad, Zainab Siddiqua, Monica Vuyyuru, Benjamin Wafula, Riaz Akhtar, Abdulbasit Fasasi, Samuel Chinonso Ubechu, Bakare Sikiru Olayinka

“…Reported model accuracies for mpox lesion classification and disease trend prediction ranged from 83 to 99.8%, underscoring the high potential of AI-based tools in this field. …”
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THE FEATURES OF QUALITATIVE AND QUANTITATIVE RECONSTRUCTION OF BUCCAL EPITHILIUM CELLULAR COMPOSITION IN A NICOTINE INTOXICATION by N.V. Gasiuk, T.N. Moshel, I.Yu. Popovich

“… To determine the cytological criteria that allow prediction of occurrence and course of inflammation of the oral mucosa and periodontal tissues, we performed cytological study of buccal epithelium of young people who have the habit smoking. …”
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Quantitative Analysis of Sulfur Elements in Mars-like Rocks Based on Multimodal Data by Yuhang Dong, Zhengfeng Shi, Junsheng Yao, Li Zhang, Yongkang Chen, Junyan Jia

“…Considering that sulfur exhibits distinct absorption bands in infrared spectra but demonstrates weak characteristic lines in LIBS spectra due to its low ionization energy, the combination of both spectral techniques enables the model to capture complementary sample features, thereby effectively improving prediction accuracy and robustness. To validate the advantages of the multimodal approach, comparative analyses were conducted against unimodal methods. …”
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Application of Energy Dispersive X-ray Fluorescence Spectroscopy in Analysis of Heavy Metals in Soil: A Review by Aosong JIANG, Longhua WU, Zhu LI

“…In the future, it is important to continue to explore the causes and magnitude of different matrix effects in various types of soils, and to optimize and improve the quantitative analysis model of ED-XRF spectroscopy; the prediction of the effectiveness of heavy metals in soil through multiple regression analysis is also a field that scholars should focus on.…”
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Research progress on shale gas productivity evaluation: concepts, methods and future directions by ZHU Suyang, PENG Zhen, DI Yunting, PENG Xiaolong, LIU Dongchen, GUAN Wenjie

“…These advancements aim to avoid the limitations in existing productivity evolution methods and support the development of robust and rational shale gas productivity evaluation models and methods, providing theoretical guidance for accurate well productivity prediction, production stabilization, and efficient resource development.…”
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UAV Trajectory Control and Power Optimization for Low-Latency C-V2X Communications in a Federated Learning Environment by Xavier Fernando, Abhishek Gupta

“…Moreover, a low-complexity UAV trajectory prediction and vehicle selection method is proposed using federated learning, which exploits related information from past trajectories. …”
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Determinação do coeficiente convectivo de transferência de calor de figos submetidos ao resfriamento rápido Determination of the convective heat transfer coefficient of fig fruits... by Mariangela Amendola, Saul Dussán-Sarria, Anderson A. Rabello

“…The objective was to compare the result with the one determined by fitting an empirical equation from the literature to the experimental data. For the prediction of the temperature, near to the center of fruits, the Fourier law model was considered. …”
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PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients by Yufeng Wang, Huifen Dang, Gongjian Zhu, Yingxia Tian

“…The model remained significant in multivariate Cox regression analysis, indicating that it could independently predict the survival of BC patients. ACSL1, BNIP3, and EMC2 were downregulated after knockdown of PDP1.ConclusionRiskScore model constructed by PDP1-ferroptosis-related genes ACSL1, BNIP3, and EMC2 is able to help predict the prognosis of BC patients.…”
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soundscape_IR: A source separation toolbox for exploring acoustic diversity in soundscapes by Yi‐Jen Sun, Shih‐Ching Yen, Tzu‐Hao Lin

“…Abstract Soundscapes contain rich acoustic information associated with animal behaviours, environmental characteristics and human activities, providing opportunities for predicting biodiversity changes and associated drivers. …”
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Casualty Analysis of the Drivers in Traffic Accidents in Turkey: A CHAID Decision Tree Model by Zeliha Cagla Kuyumcu, Hakan Aslan, Nilufer Yurtay

“…This study aims to establish a model to predict the driver’s status (survived–injured–dead) as a result of the fatal-injury type of accident. …”
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Machine learning-assisted quantitative metabolomics of West African patients with advanced breast cancer by Aboubacar Dit Tietie Bissan, Mathieu Michel, Xavier Dieu, Cinzia Bocca, Awo Emmanuela Hilda Amegonou, Fatoumata Matokoma Sidibe, Madani Ly, Bocary Sidi Koné, Nènè Oumou Kesso Barry, Kletigui Casimir Dembélé, Bakary Cissé, Bourèma Kouriba, Gilles Simard, Delphine Mirebeau-Prunier, Juan Manuel Chao de la Barca, Zahra Ouzzif, Pascal Reynier

“…The data were compared with those of 79 healthy controls using a combination of several machine learning approaches and statistical analyses. The predictive models obtained with the machine learning algorithms were comparable, with the best AUC of 0.878 obtained with ridge logistic regression using Boruta feature selection. …”
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Deep learning in microbiome analysis: a comprehensive review of neural network models by Piotr Przymus, Krzysztof Rykaczewski, Adrián Martín-Segura, Jaak Truu, Enrique Carrillo De Santa Pau, Mikhail Kolev, Mikhail Kolev, Irina Naskinova, Aleksandra Gruca, Alexia Sampri, Alexia Sampri, Marcus Frohme, Alina Nechyporenko, Alina Nechyporenko

“…These computational techniques have become essential for addressing the inherent complexity and high-dimensionality of microbiome data, which consist of different types of omics datasets. Deep learning algorithms have shown remarkable capabilities in pattern recognition, feature extraction, and predictive modeling, enabling researchers to uncover hidden relationships within microbial ecosystems. …”
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Cyclical hybrid imputation technique for missing values in data sets by Kurban Kotan, Serdar Kırışoğlu

“…Because incorrect imputation of missing data increases the error in the modeling phase and reduces the prediction performance of the model. When it comes to health, it is inevitable to choose models that show a higher success rate. …”
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