Deep Learning–Based Automated Imaging Classification of ADPKD by Youngwoo Kim, Seonah Bu, Cheng Tao, Kyongtae T. Bae, Theodore Steinman, Jesse Wei, Peter Czarnecki, Ivan Pedrosa, William Braun, Saul Nurko, Erick Remer, Arlene Chapman, Diego Martin, Frederic Rahbari-Oskoui, Pardeep Mittal, Vicente Torres, Marie C. Hogan, Ziad El-Zoghby, Peter Harris, James Glockner, Bernard King, Jr., Ronald Perrone, Neil Halin, Dana Miskulin, Robert Schrier, Godela Brosnahan, Berenice Gitomer, Cass Kelleher, Amirali Masoumi, Nayana Patel, Franz Winklhofer, Jared Grantham, Alan Yu, Connie Wang, Louis Wetzel, Charity G. Moore, James E. Bost, Kyongtae Bae, Kaleab Z. Abebe, J. Philip Miller, Paul A. Thompson, Josephine Briggs, Michael Flessner, Catherine M. Meyers, Robert Star, James Shayman, William Henrich, Tom Greene, Mary Leonard, Peter McCullough, Sharon Moe, Michael Rocco, David Wendler

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Proposal of a new classification scheme for periocular injuries by Devi Prasad Mohapatra, Friji Meethale Thiruvoth, Ravi Kumar Chittoria, S. Dinesh Kumar, Sudhanva Hemant Kumar, Senthil Kumar, Preethitha Babu, Elan Kumar

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The prognostic efficacy and improvements of the 7th edition Union for International Cancer Control tumor–node–metastasis classifications for Chinese patients with gastric cancer: Results based on a retrospective three-decade population study by Huizi Gu, Dongmei Li, Haitao Zhu, Hao Zhang, Ying Yu, Dongxue Qin, Mei Yi, Xiang Li, Ping Lu

“…This study aimed to evaluate survival trends for patients with gastric cancer in northeast China in the most recent three decades and analyze the applicability of the UICC tumor-node-metastasis (TNM) classification 7th edition for Chinese patients with gastric cancer. …”
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Classification and the diagnostics of abnormal uterine bleeding in nongravid women of reproductive age: The PALM-COEIN classification system adopted by the International Federation... by Spremović-Rađenović Svetlana, Stefanović Aleksandar, Kadija Saša, Jeremić Katarina, Sparić Radmila

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Classification from Sky: A Robust Remote Sensing Time Series Image Classification Using Spatial Encoder and Multi-Fast Channel Attention by Kwabena Sarpong, Jehoiada Kofi Jackson, Derrick Effah, Daniel Addo, Sophyani Banaamwini Yussif, Mohammad Awrangjeb, Rutherford Agbeshi Patamia, Juliana Mantebea Danso, Zhiguang Qin

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AI-Driven Plant Health Assessment: A Comparative Analysis of Inception V3, ResNet-50 and ViT with SHAP for Accurate Disease Identification in Taro by Valeria Maeda-Gutiérrez, Juan José Oropeza-Valdez, Luis C. Reveles-Gómez, Cristian Padron-Manrique, Osbaldo Resendis-Antonio, Luis Octavio Solís-Sánchez, Hector A. Guerrero-Osuna, Carlos Alberto Olvera Olvera

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Assessment of Relationship between Ankyloglossia and Sagittal Jaw Discrepancies: An Analytical Cross-Sectional Study by Thi Thuy Hong Vo, Thi Kim Duyen Hoang, Thi Trang Nguyen, Viet Anh Nguyen, Thu Tra Nguyen

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Automatic Tissue Differentiation in Parotidectomy using Hyperspectral Imaging by Wisotzky Eric L., Schill Alexander, Hilsmann Anna, Eisert Peter, Knoke Michael

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Analysis of the PointNet neural network architecture by L. A. Shchenyavskaya, D. A. Gura, R. A. Dyachenko

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Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type Classification by Jusman Yessi, Arisandy Kusumaning Putri Arif, Nur Nazilah Chamim Anna, Ardiyanto Yudhi

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From Binary to Multi-Class Classification: A Two-Step Hybrid CNN-ViT Model for Chest Disease Classification Based on X-Ray Images by Yousra Hadhoud, Tahar Mekhaznia, Akram Bennour, Mohamed Amroune, Neesrin Ali Kurdi, Abdulaziz Hadi Aborujilah, Mohammed Al-Sarem

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Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification by Lili Yang, Yi Yang, Peng Liu, Lina Wang

“…In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. …”
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Roles of Pyroptosis-Related Genes in the Diagnosis and Subtype Classification of Periodontitis by Xiaofan Cheng, Yifang Hu, Guan Gui, Xiaoya Hu, Jie Zhu, Bowei Shi, Shoushan Bu

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Fracture Line Morphology and a Novel Classification of Pilon Fractures by Jichao Liu, Chengdong Piao, Guanlu Cui, Haipeng Sun, Zhengwei Li

“…This study aimed to create a fracture map encompassing all types of Pilon fractures by three‐dimensional fracture mapping. In addition, this study conducted a finite element analysis of the normal ankle joint, and based on the distribution of fracture lines and the stress distribution at the distal tibia, proposed a new classification for Pilon fractures. …”
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Classification of OCT Images of the Human Eye Using Mobile Devices by Agnieszka Stankiewicz, Tomasz Marciniak, Nina Budna, Róża Chwałek, Marcin Dziedzic

“…The results of the classification are displayed for three neural networks, along with the respective classification times for each neural network and the associated image undergoing the classification task. …”
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Multi-Feature Facial Complexion Classification Algorithms Based on CNN by Xiyuan Cao, Delong Zhang, Chunyang Jin, Zhidong Zhang, Chenyang Xue

“…Innovative frameworks of the three algorithms can more effectively exploit facial features, improving the utilization rate of feature information and classification performance. …”
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The Classification and Formation Rate of Swift/BAT Gamma-Ray Bursts by Juan-Juan Luo, Liang Zhang, Li-Yun Zhang, Yong-Feng Huang, Jia-Quan Lin, Jun-Wang Lu, Xiao-Fei Dong

“…Here we reexamine the long/short classification of GRBs and further compare the cosmological distribution and evolution of each potential subclass. …”
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Fractal Dimension Based on Morphological Covering for Ground Target Classification by Kai Du, Xiang Fang, Wei-ping Zhang, Kai Ding

“…Experiment results demonstrate that the three proposed methods achieve more than 90% accuracy for vehicle classification.…”
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Heart Signal Analysis Using Multistage Classification Denoising Model by Ravi Raj Choudhary, Mamta Rani, Ranjit Kaur, Mahendra Bhadu

“…At the user end, binary classification of signals is performed, and if signals are abnormal then further classification is done at the clinic. …”
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Application of Neural Networks to the Classification of Pancreatic Intraductal Proliferative Lesions by Krzysztof Okoń, Romana Tomaszewska, Krystyna Nowak, Jerzy Stachura

“…We studied the efficacy of networks containing from one to three hidden layers. Using the best network, containing three hidden layers, the rate of correct classification of nuclei was 73%, and the rate of misdiagnosis was 3%; in 24% the network response was ambiguous. …”
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