Efficacy comparison of immune combination therapies in subgroups for advanced hepatocellular carcinoma patients: Systematic review and network meta-analysis. by Yani Wang, Wanyee Lau, Yafei Li, Yichen Tian, Yongrong Lei, Feng Xia, Jianhua Wang

“…This study aims to employ a rigorous network meta-analysis (NMA) approach to systematically evaluate the effectiveness of immune-combination therapies among patients with advanced hepatocellular carcinoma, taking into account their varying clinico-characteristics.…”
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A Self-Interpretable Deep Learning Model for Seizure Prediction Using a Multi-Scale Prototypical Part Network by Yikai Gao, Aiping Liu, Lanlan Wang, Ruobing Qian, Xun Chen

“…Furthermore, we assign different sizes to the prototypes in latent space to capture the multi-scale features of EEG signals. To the best of our knowledge, this is the first study that develops a self-interpretable deep learning model for seizure prediction, other than the existing post hoc interpretation studies. …”
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Development of a Transfer Learning-Based, Multimodal Neural Network for Identifying Malignant Dermatological Lesions From Smartphone Images by Jiawen Deng, Eddie Guo, Heather Jianbo Zhao, Kaden Venugopal, Myron Moskalyk

“…Analysis of permutation importance showed that key clinical features influential for the clinical data-based network included bleeding, lesion elevation, patient age and recent lesion growth. …”
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GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data by Kai Wang, Yulong Li, Fei Liu, Xiaoli Luan, Xinglong Wang, Jingwen Zhou

“…To evaluate the performance of GRLGRN, we compared it with prevalent models and performed ablation experiments on seven cell-line datasets with three ground-truth networks. …”
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UPE-Net: A Spatial Information Enhanced Network for Ulva Prolifera Extraction From GF-1 WFV Images by Hui Sheng, Manman Jia, Shiqing Wei, Lie Sun, Mingming Xu, Shanwei Liu, Jianhua Wan

“…Third, a detail-enhanced attention block is incorporated to enhance the learning of crucial spatial and detail features during the decoding process. The performance of the proposed model was evaluated using the Gaofen-1 wide field view Ulva prolifera dataset. …”
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A dual-task segmentation network based on multi-head hierarchical attention for 3D plant point cloud by Dan Pan, Baijing Liu, Lin Luo, An Zeng, Yuting Zhou, Kaixin Pan, Zhiheng Xian, Yulun Xian, Yulun Xian, Licheng Liu

“…Also, the dual-task framework employs Multi-Value Conditional Random Field (MV-CRF) to enable semantic segmentation of stem-leaf and individual leaf identification through the DSN architecture when processing manually-annotated 3D point cloud data. The network features a dual-branch architecture: one branch predicts the semantic class of each point, while the other embeds points into a high-dimensional vector space for instance clustering. …”
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Multi-Omics Analysis Identifies Immune Regulatory Networks in Sepsis-Associated Liver Injury: Experimental Validation and Clinical Relevance by Hong Y, Chen Q, Xie H, Ma M, Gan S, Zhang Y, Xu Z

“…Protein-protein interaction (PPI) network analysis demonstrated that these genes form a synergistic regulatory network involving NF-κB, JAK-STAT, and other key pathways, with notable features including the IL2RB-XCL1 positive feedback loop and the opposing effects of PTGDR isoforms (DP1/DP2). …”
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A Technical Note on AI-Driven Archaeological Object Detection in Airborne LiDAR Derivative Data, with CNN as the Leading Technique by Reyhaneh Zeynali, Emanuele Mandanici, Gabriele Bitelli

“…This technical note comprehensively reviews 45 recent studies to critically examine the integration of Machine Learning (ML) and Deep Learning (DL) techniques, particularly Convolutional Neural Networks (CNNs), with airborne LiDAR derivatives for automated archaeological feature detection. …”
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Automated Detection of High Frequency Oscillations in Intracranial EEG Using the Combination of Short-Time Energy and Convolutional Neural Networks by Dakun Lai, Xinyue Zhang, Kefei Ma, Zichu Chen, Wenjing Chen, Heng Zhang, Han Yuan, Lei Ding

“…A new methodology is presented in this paper for the automated detection of HFOs based on their 2D time–frequency map employing the short-time energy (STE) estimation and the convolutional neural network (CNN) classification algorithm. The effectiveness and usefulness of the proposed method are evaluated using the clinical iEEG data acquired from five patients (28.4 ± 13.0 years) with medically intractable epilepsy. …”
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Adaptive Hierarchical Multi-Headed Convolutional Neural Network With Modified Convolutional Block Attention for Aerial Forest Fire Detection by Md. Najmul Mowla, Davood Asadi, Shamsul Masum, Khaled Rabie

“…Convolutional Neural Networks (CNNs) have demonstrated potential in this domain but encounter limitations when addressing varying scales, resolutions, and complex spatial dependencies inherent in wildfire datasets. …”
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Integrating Fractional-Order Hopfield Neural Network with Differentiated Encryption: Achieving High-Performance Privacy Protection for Medical Images by Wei Feng, Keyuan Zhang, Jing Zhang, Xiangyu Zhao, Yao Chen, Bo Cai, Zhengguo Zhu, Heping Wen, Conghuan Ye

“…Fractional-order Hopfield neural networks (HNNs) demonstrate unique advantages in IE. …”
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Artificial intelligence for herbicide recommendation: Case study for the use of clomazone in Brazilian soils by Hamurábi Anizio Lins, Matheus de Freitas Souza, Lucrecia Pacheco Batista, Luma Lorena Loureiro da Silva Rodrigues, Francisca Daniele da Silva, Bruno Caio Chaves Fernandes, Stefeson Bezerra de Melo, Paulo Sergio Fernandes das Chagas, Daniel Valadão Silva

“…In this study, the efficiency of Artificial Neural Networks (ANNs) was evaluated as a tool to predict clomazone sorption in different Brazilian soils. …”
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Big Data Analytics for Uncovering Voxel Connectivity Patterns in Attention Deficit Hyperactivity Disorder by Caraka RE, Supardi K, Gio PU, Isnaniawardhani V, Chen RC, Djatmiko B, Pardamean B

“…Feature selection was performed using Boruta, Random Forest in combination with DALEX explainability tools, and Neural Networks. …”
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Design and trial of precision spraying system for weeds in winter wheat field at tillering stage by Bo Li, Peijie Guo, Yu Chen, Jun Chen, Haiying Wang, Jing Zhang, Zhixing Zhang

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Evaluation of fixed assets of electric power enterprises-operators of the distribution system under the conditions of the post-war reconstruction of Ukraine by R.L.

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Generation of High-Resolution Surface Soil Moisture over Mountain Areas by Spatially Downscaling Remote Sensing Products Based on Land Surface Temperature–Vegetation Index Feature... by Junfei Cai, Wei Zhao, Tao Ding, Gaofei Yin

“…Through the direct validation with the in situ soil moisture measurements from the Snow Telemetry network, the downscaled results show better performance than other previous methods, with the average value of the correlation coefficient, root-mean-square error, and unbiased root-mean-square error derived at the site level of 0.47, 0.103 m3/m3, and 0.056 m3/m3, respectively. …”
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Towards interpretable drug interaction prediction via dual-stage attention and Bayesian calibration with active learning by Rongpei Li, Yufang Zhang, Heqi Sun, Shenggeng Lin, Guihua Jia, Yitian Fang, Chen Zhang, Xiaotong Song, Jianwei Zhao, Lyubin Hu, Yajing Yuan, Xueying Mao, Jiayi Li, Aman Kaushik, Dandan An, Dongqing Wei

“…Bayesian calibration improved adverse event detection accuracy (94% vs. 54% AUC), while network pharmacology revealed key molecular mechanisms through enzyme-transporter interactions. …”
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Optimized deep learning approach for lung cancer detection using flying fox optimization and bidirectional generative adversarial networks by Manal Abdullah Alohali, Hamed Alqahtani, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K., Jaehyuk Cho

“…Computer-aided diagnosis (CAD) systems have significantly improved early cancer detection, but limitations such as high-dimensional feature sets and overfitting issues persist. This study presents an optimised deep learning approach for lung cancer classification, integrating flying fox optimization (FFXO) for feature selection and bidirectional generative adversarial networks (Bi-GAN) for classification. …”
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DS-YOLO: A dense small object detection algorithm based on inverted bottleneck and multi-scale fusion network by Hongyu Zhang, Guoliang Li, Dapeng Wan, Ziyue Wang, Jinshun Dong, Shoujun Lin, Lixia Deng, Haiying Liu

“…Firstly, to enhance the dense small objects’ feature extraction capability of backbone network, the paper proposes a lightweight backbone. …”
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Attention LinkNet-152: a novel encoder-decoder based deep learning network for automated spine segmentation by Aqsa Dastgir, Wang Bin, Muhammad Usman Saeed, Jinfang Sheng, Luo Site, Haseeb Hassan

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