Performance Evaluation of 3-D Convolutional Neural Network for Multitemporal Flood Classification Framework With Synthetic Aperture Radar Image Data by Dodi Sudiana, Indra Riyanto, Mia Rizkinia, Rahmat Arief, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo, Ketut Wikantika

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Fine-scale forest classification with multi-temporal sentinel-1/2 imagery using a temporal convolutional neural network by Rongfei Duan, Chunlin Huang, Peng Dou, Jinliang Hou, Ying Zhang, Juan Gu

“…However, spectral similarity between different vegetation types and the issue of mixed pixels in medium-resolution satellite imagery remain significant challenges for fine-scale forest classification. This study focused on the Tao River National Nature Reserve in southern Gansu Province, China, where over 6,000 vegetation samples were collected. …”
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EMNet: A Novel Few-Shot Image Classification Model with Enhanced Self-Correlation Attention and Multi-Branch Joint Module by Fufang Li, Weixiang Zhang, Yi Shang

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Novel method for classification of prion diseases by detecting PrPres signal patterns from formalin-fixed paraffin-embedded samples by Sachiko Koyama, Kaoru Yagita, Hideomi Hamasaki, Hideko Noguchi, Masahiro Shijo, Kosuke Matsuzono, Kei-Ichiro Takase, Keita Kai, Shin-Ichi Aishima, Kyoko Itoh, Toshiharu Ninomiya, Naokazu Sasagasako, Hiroyuki Honda

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Development and Validation of a Novel Classification System and Prognostic Model for Open Traumatic Brain Injury: A Multicenter Retrospective Study by Yuhui Chen, Li Chen, Liang Xian, Haibing Liu, Jiaxing Wang, Shaohuai Xia, Liangfeng Wei, Xuewei Xia, Shousen Wang

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Evaluation of Machine Learning Algorithms for Classification of Visual Stimulation-Induced EEG Signals in 2D and 3D VR Videos by Mingliang Zuo, Xiaoyu Chen, Li Sui

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Pan-cancer analysis of the transcriptional expression of histone acetylation enzymes in solid tumors defines a new classification scheme for gliomas by Junhao Zhang, Lingbo Li, Aiwei Tang, Chucheng Wang, Yupeng Wang, Yongqi Hu, Guangting He, Guangting He, Wangjun Liao, Wangjun Liao, Wangjun Liao, Rui Zhou

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Comparison Between Convolutional Neural Network CNN and SVM in Skin Cancer Images Recognition by Zaid Ghazi Hadi, Ahmed R. Ajel, Ayad Q. Al-Dujaili

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Fractionation of rare earth elements in tropical soils from marine mudstone along a toposequence by Marvin D. Cascante, Cho-Yin Wu, Zeng-Yei Hseu

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Application research of convolutional neural network and its optimization in lightning electric field waveform recognition by Caixia Wang, Xiaoyi Zhang, Hui Yang, Jinyuan Guo, Jia Xu, Zhuling Sun

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Individual management and prognostic assessment for long-term outcomes using a novel classification system of craniopharyngiomas: a retrospective study of single institution by Sen Zhang, Bo Xie, Yi He, Xingshu Zhang, Gu Gong, Mingrui Li, Yinhua Chen, Guodong Tang, Chi Zhang, Chaoying Qin, Qing Liu

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AI-Driven Innovations in Tourism: Developing a Hybrid Framework for the Saudi Tourism Sector by Abdulkareem Alzahrani, Abdullah Alshehri, Maha Alamri, Saad Alqithami

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Symptoms indicative of early knee osteoarthritis after ACL reconstruction: descriptive analysis of the SHIELD cohort by Anna Cronström, May Arna Risberg, Martin Englund, Dorthe B. Strauss, Paul Neuman, Carl Johan Tiderius, Eva Ageberg

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Novel Algorithm for Surgical Management of Cervical Ossification of Posterior Longitudinal Ligament: A Retrospective Cohort Study With 2‐Year Follow‐Up by Zhuyun Cai, Hui Kang, Lei Quan, Yilong Ren, Meng Fang, Yixuan Tan, Haochen Zhang, Xuhui Zhou, Jun Ma

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Humeral Capitellum Fractures in Adolescents: A Study of 6 Cases Treated by Open Reduction and Internal Fixation with Bioabsorbable Nails by Łukasz Wiktor, Ryszard Tomaszewski

“…We retrospectively evaluated a group of 6 skeletally immature patients aged 10.6–15.3 treated at our department from January 2015 to December 2021. …”
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Concentrations of Selected Adipokines, Interleukin-6, and Vitamin D in Patients with Papillary Thyroid Carcinoma in Respect to Thyroid Cancer Stages by Jakub Warakomski, Ewa Romuk, Barbara Jarząb, Jolanta Krajewska, Lucyna Siemińska

“…We searched for associations between the adipokines, IL-6, vitamin D, anthropometric parameters, and TNM AJCC/UICC 2017 classification in 177 patients diagnosed with PTC (151 women and 26 men). …”
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Pan-cancer characterization of m6A-mediated regulation of T cell exhaustion dynamics and clinical relevancies in human cancers by Weiping Ji, Ye Fang, Liwei Chen, Yitong Zheng, Yifei Pei, Changqiu Mei, Meng Zhou

“…T cell exhaustion (TEX) is a major barrier to effective immunotherapy. The role of N6-methyladenosine (m6A) modification in regulating immune cell function has been recognized, but its impact on TEX dynamics across cancer types and clinical outcomes remains unclear. …”
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Comparative Study of Protein Expression Levels of Five Plaque Biomarkers and Relation with Carotid Plaque Type Classification in Patients after Carotid Endarterectomy by Konstantinos Kyriakidis, Pavlos Antoniadis, Sohail Choksy, Rigini M. Papi

“…The gender and age effect was also examined. MMP-1, MMP-9, and IL-6 were expressed in higher levels compared to OPN and TNFa as well as in symptomatic (with type II and III carotid plaque classification) than asymptomatic (type IV) patients with differences considered statistically significant (P values <0.05). …”
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Characteristics That Predict Psoriatic Arthritis by the Classification Criteria for Psoriatic Arthritis in Patients With Juvenile Idiopathic Arthritis 18 Years After Disease Onset by Agnes Szentpetery, Mia Glerup, Kristiina Aalto, Ellen D. Arnstad, Anders Fasth, Troels Herlin, Charlotte Myrup, Ellen Nordal, Suvi Peltoniemi, Marite Rygg, Veronika Gjertsen Rypdal, Lillemor Berntson

“…Results Among the 510 patients enrolled, 434 participated in the 18‐year follow‐up, 28 (6.5%) met the ILAR criteria, and 41 (9.4%) fulfilled the CASPAR criteria. …”
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Fake News Detection and Classification: A Comparative Study of Convolutional Neural Networks, Large Language Models, and Natural Language Processing Models by Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios K. Nasiopoulos

“…Our results demonstrate that the fine-tuned GPT-4 Omni models achieve 98.6% accuracy, significantly outperforming traditional models like CNNs, which achieved only 58.6%. …”
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