Deep learning-based automated segmentation and quantification of the dural sac cross-sectional area in lumbar spine MRI by George Ghobrial, Christian Roth

“…This study evaluates the efficacy of deep learning models for automating DSCA measurements in lumbar spine MRIs to enhance diagnostic precision and alleviate the workload of radiologists.MethodsFor algorithm development and assessment, we utilized two extensive, anonymized online datasets: the “Lumbar Spine MRI Dataset” and the SPIDER-MRI dataset. …”
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Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers by Koji Ikeuchi, Daiki Kakinuma, Yosuke Nakamura, Shingo Numata, Takafumi Mochizuki, Keijiro Kubota, Masaki Yasukawa, Toshihiro Nemoto, Toshio Koike

“…Therefore, we developed a system that can accurately predict when river water levels will reach the Flood Risk Level (FRL). …”
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Multi-scale adversarial diffusion network for image super-resolution by Yanli Shi, Xianhe Zhang, Yi Jia, Jinxing Zhao

“…This ensures that the predicted images exhibit more realistic texture details. …”
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Automated recognition and segmentation of lung cancer cytological images based on deep learning. by Qingyang Wang, Yazhi Luo, Ying Zhao, Shuhao Wang, Yiru Niu, Jinxi Di, Jia Guo, Guorong Lan, Lei Yang, Yu Shan Mao, Yuan Tu, Dingrong Zhong, Pei Zhang

“…Thus, in this study, we developed a model for intraoperative cytological segmentation of pulmonary lesions based on the YOLOv8 algorithm, which labels each instance by segmenting the image at the pixel level. …”
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Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model by Yuhong Ouyang, Man Li, Wenqian Kang, Xiangbei Che, Ruixian Ye

“…The long- and short-term memory network is then used to predict the operation trend of the distribution network under normal operation and fault disturbance. …”
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Models for a Fast Computation of Internal Overvoltages in Medium-Frequency Transformers by Bastian Korthauer, Jurgen Biela

“…Therefore, this paper presents an analytical approach to compute impedance and capacitance matrices for the equivalent networks, focusing on an efficient algorithm to compute the capacitance matrix as well as an appropriate length scaling of the calculated per-unit-length matrices. …”
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Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review by Catalina Gomez, Sue Min Cho, Shichang Ke, Chien-Ming Huang, Mathias Unberath

“…Leveraging Artificial Intelligence (AI) in decision support systems has disproportionately focused on technological advancements, often overlooking the alignment between algorithmic outputs and human expectations. A human-centered perspective attempts to alleviate this concern by designing AI solutions for seamless integration with existing processes. …”
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Winter arctic sea ice volume decline: uncertainties reduced using passive microwave-based sea ice thickness by Clement Soriot, Martin Vancoppenolle, Catherine Prigent, Carlos Jimenez, Frédéric Frappart

“…Abstract Arctic sea ice volume (SIV) is a key climate indicator and memory source in sea ice predictions and projections, yet suffering from large observational and model uncertainty. …”
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An analytical examination of the performance assessment of CNN-LSTM architectures for state-of-health evaluation of lithium-ion batteries by Arun Jose, Sonam Shrivastava

“…This research specifically examines the potential of the convolutional neural network–long short-term memory algorithm to improve the precision of State of Health forecasts for the battery model. …”
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In silico and ex vivo approaches indicate immune pressure on capsid and non-capsid regions of coxsackie B viruses in the human system. by Rhiannon Kundu, Robin Knight, Meenakshi Dunga, Mark Peakman

“…To address this knowledge gap, we augmented conventional HLA-binding predictive algorithm-based epitope discovery by cross-referencing epitopes with sites of positive natural selection within the CBV3 viral genome, identified using mixed effects models of evolution. …”
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Design and Optimization of a Piezoelectric Stick-Slip Actuator with Distributed Compliance by Tingting Ye, Zhao Feng, Yangmin Li

“…Then, its dominant performances are predicted through finite element analysis, including the step size and the first natural frequency. …”
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Determination of disintegration time using formulation data for solid dosage oral formulations via advanced machine learning integrated optimizer models by Mohammed Ghazwani, Umme Hani

“…Data preprocessing involved Min-Max normalization, outlier detection via Elliptic Envelope, and feature selection using Conditional Mutual Information, with hyperparameters optimized through the Water Cycle Algorithm. Performance was assessed using R², RMSE, and MAE across train, validation, and test sets, with 95% confidence intervals confirming robust predictions. …”
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Tumor Intrinsic Immunogenicity Suppressor SETDB1 Worsens the Prognosis of Patients with Hepatocellular Carcinoma by Chang-Qing Yin, Chun-Qing Song

“…In conclusion, the upregulation of SETDB1 is associated with a poorer prognosis in HCC patients and inversely correlates with immune cell infiltration, potentially serving as a predictive marker for immunotherapy response.…”
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The Face and number plate recognition for car anti-theft by Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen

“…The system automatically predicts whether the driver is valid with the registration number plate. …”
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In Silico identification and modelling of FDA-approved drugs targeting T-type calcium channels. by Pedro Fong, Susana Roman Garcia, Melanie I Stefan, David C Sterratt

“…We used the automated docking suite GOLD v5.5 with the genetic algorithm to simulate molecular docking and predict the protein-ligand binding modes, and the ChemPLP empirical scoring function to estimate the binding affinities of 2,115 FDA-approved drugs to the human Cav3.1 channel. …”
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Machine Learning Classification of 3D Intracellular Trafficking Using Custom and Imaris-Derived Motion Features by Oleg Kovtun

“…<b>Methods:</b> This study extends a previously established two-dimensional, machine learning-based diffusional fingerprinting approach into a three-dimensional framework to overcome this limitation. It presents an algorithm that predicts intracellular motion types based on a comprehensive feature set, including custom statistical descriptors and standard Imaris-derived trajectory features, which capture subtle variations in individual trajectories. …”
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Physics-based Forecasting of Tomorrow’s Solar Wind at 1 au by Igor V. Sokolov, Tamas I. Gombosi

“…We derive the modified governing equations for both hydrodynamics and magnetohydrodynamics and present a new numerical algorithm that solves the modified governing equations. …”
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YOLO Model-Based Eye Movement Detection During Closed-Eye State by Shigui Zhang, Junhui He, Yuanwen Zou

“…Our tracker achieved a mean distance error of 0.77 mm, with 90% of predicted eye position distances having an error of less than 1.67 mm, enabling real-time tracking at 30 frames per second. …”
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The Impact of Road Functions on Road Congestions Based on POI Clustering: An Empirical Analysis in Xi’an, China by Hui Zhu, Kaiqi Zhang, Changjun Wang, Lujin Jia, Siyu Song

“…We adopted the DBSCAN algorithm to cluster POIs and use the mixed POI clusters to label the socio-economic functions of roads. …”
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The Face and number plate recognition for car anti-theft by Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen

“…The system automatically predicts whether the driver is valid with the registration number plate. …”
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