Efficacy and safety of thermal ablation for Bethesda III/IV thyroid nodules: a retrospective study by Song Li, Ying Wei, Zhen-long Zhao, Li-li Peng, Yan Li, Ming-an Yu

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Packet Classification by Multilevel Cutting of the Classification Space: An Algorithmic-Architectural Solution for IP Packet Classification in Next Generation Networks by Motasem Aldiab, Emi Garcia-Palacios, Danny Crookes, Sakir Sezer

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Design of a Classification Recognition Model for Bone and Muscle Anatomical Imaging Based on Convolutional Neural Network and 3D Magnetic Resonance by Ting Pan, Yang Yang

“…In this paper, we use convolutional neural networks to conduct in-depth research and analysis on the classification and recognition of bone and muscle anatomical imaging graphics of 3D magnetic resonance and design corresponding models for practical applications. …”
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The Class III Peroxidase Gene Family in <i>Populus simonii</i>: Genome-Wide Identification, Classification, Gene Expression and Functional Analysis by Lu Han, Yishuang Ren, Xinru Bi, Guowei Yao, Jinwang Zhang, Hongtao Yuan, Xiaoyu Xie, Junbo Chen, Yunchang Zhang, Sitong Du, Wanying Chen, Kewei Cai, Xiyang Zhao

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Chronic Inflammation Index-Based Tumor Subsite Classification Correlated with Chemotherapy Benefit and Survival Outcomes in Stage II-III Colorectal Cancer by Lu Y, Ye QY, Mei O, Li YN, Peng Y, Ying HQ, Cheng XX

“…Ying Lu,1,&amp;ast; Qiu-Ying Ye,1– 3,&amp;ast; Ou Mei,4,&amp;ast; Ya-Nan Li,1 Yue Peng,1 Hou-Qun Ying,1,3,5 Xue-Xin Cheng1 1Department of Clinical Laboratory, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People’s Republic of China; 2Department of Medical Technology, Jiangxi Medical College, Shangrao, 334000, People’s Republic of China; 3Department of Laboratory Medicine, Central Hospital of Shangrao City, Shangrao, 334000, People’s Republic of China; 4Department of Orthopedics, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, 330006, People’s Republic of China; 5Shangrao Medical Center, The Second Affiliated Hospital of Nanchang University, Shangrao, 334000, People’s Republic of China&amp;ast;These authors contributed equally to this workCorrespondence: Xue-Xin Cheng, Department of Clinical Laboratory, Immunity and Inflammation Key Laboratory of Jiangxi Province, The Second Affiliated Hospital of Nanchang University, No. 1 of Minde Road, Nanchang, 330006, People’s Republic of China, Tel/Fax +86 0791-86297662, Email cxxncu@163.com Hou-Qun Ying, Department of Clinical Laboratory, Immunity and Inflammation Key Laboratory of Jiangxi Province, The Second Affiliated Hospital of Nanchang University, No. 1 of Minde Road, Nanchang, 330006, People’s Republic of China, Tel/Fax +86 0791-86297662, Email yinghouqun2013@163.comPurpose: This study aimed to develop and validate an integrated inflammatory prognostic index and to investigate associations between primary tumor location, chronic inflammatory status, adjuvant chemotherapy response, and survival outcomes in stage II–III colorectal cancer (CRC).Patients and Methods: A total of 1413 stage II–III CRC patients who underwent radical resection were enrolled and divided into discovery and validation cohorts. …”
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Enhancing Cervical Cancer Classification: Through a Hybrid Deep Learning Approach Integrating DenseNet201 and InceptionV3 by Abhiram Sharma, R. Parvathi

“…This paper proposes a hybrid deep learning model integrating DenseNet201 and InceptionV3 to address the challenges in achieving accurate and reliable cervical cancer classification. …”
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Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification by Kuan-Hsun Lin, Tzu-Hang Kao, Lei-Chi Wang, Chen-Tsung Kuo, Paul Chih-Hsueh Chen, Yuan-Chia Chu, Yi-Chen Yeh

“…All three models showed a tendency to assign variants to higher evidence levels, suggesting a propensity for overclassification. …”
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Evaluating the efficacy of three classical EEG paradigms in the discrimination of bipolar depression by Chen Yang, Yao Pi, Weijie Wang, Ying Huang, Nan Tang, Hong Wang, Shenglin Wen

“…ObjectiveGiven the lack of consensus regarding the optimal EEG paradigm for identifying bipolar depression (BD), this study sought to systematically evaluate the efficacy of three classic EEG paradigms—eyes open, eyes closed, and free viewing—in diagnosing BD.MethodsEEGs were collected from 28 individuals diagnosed with BD and 42 healthy controls(HCs) across three experimental conditions: eyes closed, eyes open, and free viewing. …”
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3D Parametric Modelling based on Point Cloud for the Interpretation of the Archaeological Remains by Fausta Fiorillo, Corinna Rossi

“…The ensuing 3D modelling allows a morphological/geometric analysis and an interpretation/classification of the architectonic proprieties (features typologies and styles). …”
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A classification of cranio facio cervical (branchial) clefts (Bangalore classification) by S A Subramani, B S Murthy

“…The Clinical presentation of Clefts in the head and neck regions in our series of 146 cases, 3. The study of clefts under Rare craniofacial, Branchial [Cervical] and Classifications by various Authors and 4. …”
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A classification of cranio facio cervical (branchial) clefts (Bangalore classification) by Subramani S, Murthy B

“…The Clinical presentation of Clefts in the head and neck regions in our series of 146 cases, 3. The study of clefts under Rare craniofacial, Branchial [Cervical] and Classifications by various Authors and 4. …”
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Stridulatory Organs and Sound Recognition of Three Species of Longhorn Beetles (Coleoptera: Cerambycidae) by Jia-Quan Wei, Xiao-Yun Wang, Xia-Lin Zheng, Xin Tong

“…Linear prediction cepstral coefficients (LPCC) and Mel frequency cepstral coefficients (MFCC) were used to extract the sound features, and the support vector machine (SVM) model was used to identify the sounds of three species. The results showed that the stridulatory organs of three species of longhorn beetles differed in morphology and time domain, and the combination of MFCC and SVM had a better recognition ability. …”
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Evaluation of gene expression classification studies: factors associated with classification performance. by Putri W Novianti, Kit C B Roes, Marinus J C Eijkemans

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A three-subtype prognostic classification based on base excision repair and oxidative stress genes in lung adenocarcinoma and its relationship with tumor microenvironment by Wen Rao, Qin Zhang, Xiaoyan Dai, Yuxin Yang, Zhang Lei, Xunjie Kuang, He Xiao, Jianwu Zhu, Yanli Xiong, Dong Wang, Lujie Yang

“…The three-subtype classifications based on BER and oxidative stress gene expression offers potential for predicting the survival and response to immunotherapy of LUAD patients.…”
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Three-Dimensional Automated Breast Ultrasound (ABUS) Tumor Classification Using a 2D-Input Network: Soft Voting or Hard Voting? by Shaode Yu, Xiaoyu Liang, Songnan Zhao, Yaoqin Xie, Qiurui Sun

“…Breast cancer is a global threat to women’s health. Three-dimensional (3D) automated breast ultrasound (ABUS) offers reproducible high-resolution imaging for breast cancer diagnosis. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

Subjects: “…image classification…”
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Image recognition method of cashmere and wool based on SVM-RFE selection with three types of features by Zhu Yaolin, Liu Kainan, Gu Meihua, Zhang Kaibing, Hu Gang

“…Our approach achieves a recognition accuracy of 98.06%, which is 8.34% higher than the traditional two-feature method and 6.12% higher than the three-feature method, both without feature selection. …”
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Enhancing skin lesion classification: a CNN approach with human baseline comparison by Deep Ajabani, Zaffar Ahmed Shaikh, Amr Yousef, Karar Ali, Marwan A. Albahar

“…A CNN model utilizing the EfficientNetB3 backbone is trained on datasets from the ISIC-2019 and ISIC-2020 SIIM-ISIC melanoma classification challenges and evaluated on a 150-image test set. …”
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Integrating advanced deep learning techniques for enhanced detection and classification of citrus leaf and fruit diseases by Archna Goyal, Kamlesh Lakhwani

“…Abstract In this study, we evaluate the performance of four deep learning models, EfficientNetB0, ResNet50, DenseNet121, and InceptionV3, for the classification of citrus diseases from images. …”
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Alzheimer’s Detection through 3D Convolutional Neural Networks by Ryan Hogan, Christoforos Christoforou

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