Deep Learning Based Automatic Ankle Tenosynovitis Quantification from MRI in Patients with Psoriatic Arthritis: A Feasibility Study by Saeed Arbabi, Vahid Arbabi, Lorenzo Costa, Iris ten Katen, Simon C. Mastbergen, Peter R. Seevinck, Pim A. de Jong, Harrie Weinans, Mylène P. Jansen, Wouter Foppen

“…However, visual scoring s variability. This study evaluates a fully automated, deep-learning approach for ankle tenosynovitis segmentation and volume-based quantification from MRI in psoriatic arthritis (PsA) patients. …”
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Development and multicenter validation of an AI driven model for quantitative meibomian gland evaluation by Li Li, Kunhong Xiao, Taichen Lai, Kunfeng Lai, Jiawen Lin, Zongyuan Ge, Lingyi Liang, Hao Huang, Xiaoshan Zhang, Li Liu, Yujie Wang, Xianwen Shang, Mingguang He, Ying Xue, Zhuoting Zhu

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Adapting a global plant identification model to detect invasive alien plant species in high-resolution road side images by Vincent Espitalier, Jean-Christophe Lombardo, Hervé Goëau, Christophe Botella, Toke Thomas Høye, Mads Dyrmann, Pierre Bonnet, Alexis Joly

“…Deep learning technologies show promise for processing this data efficiently, but the choice of approach significantly affects both computational and human resource costs. Object detection and segmentation methods require costly annotations, making them impractical for scaling to the thousands of invasive species worldwide. …”
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Artificial Intelligence Precision Recognition and Auxiliary Diagnosis of Dental X-ray Panoramic Images Based on Deep Learning by Liu Riming, Gao Zhenshan

“…Objective: This study aims to explore the application of deep learning algorithms in dental X-ray panoramic images, particularly for the automatic segmentation of dental caries and identification of wisdom tooth types, in order to improve the accuracy and efficiency of dental diagnosis and assist doctors in formulating precise treatment plans. …”
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Deep Learning Strategy for UAV-Based Multi-Class Damage Detection on Railway Bridges Using U-Net with Different Loss Functions by Yong-Hyoun Na, Doo-Kie Kim

“…To enable multi-class segmentation, the U-Net model was trained using three different loss functions: Cross-Entropy Loss, Focal Loss, and Intersection over Union (IoU) Loss. …”
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Among Artificial Intelligence/Machine Learning Methods, Automated Gradient-Boosting Models Accurately Score Intraoral Plaque in Non-Standardized Images by Eric Coy, William Santo, Bonnie Jue, Helen Betts, Francisco Ramos-Gomez, Stuart A. Gansky

“…Area-under-the-curve receiver operating characteristic (AUC-ROC) curve and R2 determined the best classification and regression models, respectively, compared to calibrated dentist researcher ratings. Training time was a secondary metric. Manual segmentation used Photoshop’s lasso tool. …”
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Mechanism of Influence of Spatial Perception on Residents’ Emotion in Child-Friendly Urban Streets of Fuzhou City by Shaofeng CHEN, Zhengyan CHEN, Yuhan XU, Zheng DING

“…For FCN-RF Semantic Segmentation, street view images are processed by fully convolutional networks to quantify 10 spatial metrics, validated against human-scored safety perceptions via random forest-based adversarial training; for XGBoost-SHAP Interpretability Framework, the nonlinear relationships between 12 street environment indicators and emotional indices are modeled through extreme gradient boosting, with SHapley additive explanations (SHAP) decoding feature contributions and interaction effects. …”
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Integrating radiomics features and CT semantic characteristics for predicting visceral pleural invasion in clinical stage Ia peripheral lung adenocarcinoma by Fengnian Zhao, Yunqing Zhao, Zhaoxiang Ye, Qingna Yan, Haoran Sun, Guiming Zhou

“…Abstract Objectives The aim of this study was to non-invasively predict the visceral pleural invasion (VPI) of peripheral lung adenocarcinoma (LA) highly associated with pleura of clinical stage Ia based on preoperative chest computed tomography (CT) scanning. …”
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An Important Cause of Blindness in Children: Open Globe Injuries by Meral Yildiz, Sertaç Argun Kıvanç, Berna Akova-Budak, Ahmet Tuncer Ozmen, Sadık Gorkem Çevik

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Label-free metabolic fingerprinting of motile mammalian spermatozoa with subcellular resolution by Fitore Kusari, Lenka Backova, Dalibor Panek, Ales Benda, Zdenek Trachtulec

“…We trained machine learning for automated image segmentation and generated metabolic fingerprints using object-based phasor analysis. …”
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Are Artificial Intelligence Models Listening Like Cardiologists? Bridging the Gap Between Artificial Intelligence and Clinical Reasoning in Heart-Sound Classification Using Explain... by Sami Alrabie, Ahmed Barnawi

“…To the best of our knowledge, this is the first study conducted on a manually segmented dataset, which objectively evaluates the model’s behavior using XAI and explores performance enhancement by combining attention mechanisms with pretrained models. …”
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Proposal of a flood damage road detection method based on deep learning and elevation data by Jun Sakamoto

“…Our results showed that the F-score was higher, 89%–91%, when we targeted only road segments with 15 m or less. Moreover, visualizing in GIS facilitated the classification of inundated roads, even within the same 100-m mesh, which is a relevant finding that complements deep learning object detection.…”
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A Novel Equivariant Self-Supervised Vector Network for Three-Dimensional Point Clouds by Kedi Shen, Jieyu Zhao, Min Xie

“…We demonstrate through experiments that our network can accurately detect the orientation and pose change of point clouds and visualize the latent features. Moreover, it performs well in invariant tasks such as classification and category-level segmentation.…”
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Automated Quantification of Retinopathy of Prematurity Stage via Ultrawidefield OCT by Spencer S. Burt, BA, Aaron S. Coyner, PhD, Elizabeth V. Roti, BS, Yakub Bayhaqi, PhD, John Jackson, MD, Mani K. Woodward, MS, Shuibin Ni, PhD, Susan R. Ostmo, MS, Guangru Liang, BS, Yali Jia, PhD, David Huang, MD, Michael F. Chiang, MD, Benjamin K. Young, MD, Yifan Jian, PhD, John Peter Campbell, MD

“…The ANVTV was manually segmented. A set of 3347 B-scans and corresponding manual segmentations from 12 volumes from 6 patients were used to train an automated segmentation tool using a U-Net. …”
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Sketch Face Recognition Method Based on Local-Global Adapter by Huanyu Bian, Boqian Lv, Yanan Guo, Benkui Zhang, Kangning Du

“…In addition, we propose a two-stage training strategy to fully utilize the LGAdapter to obtain more accurate visual features. …”
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Long-Term Outcomes of Intentional Head Trauma in Infants: A Comprehensive Follow-Up of Medical, Developmental, Psychological, and Legal Perspectives by Göksel Vatansever, Ezgi Özalp Akın, Pınar Bingöl Kızıltunç, Didem Behice Öztop, Kezban Karabağ, Seda Topçu, Betül Ulukol

“…Anterior and posterior segment evaluations and visual field examinations were conducted in the visual assessment. …”
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Leveraging Artificial Intelligence and Clinical Laboratory Evidence to Advance Mobile Health Applications in Ophthalmology: Taking the Ocular Surface Disease as a Case Study by Mini Han Wang, Yi Pan, Xudong Jiang, Zhiyuan Lin, Haoyang Liu, Yunxiao Liu, Jiazheng Cui, Jiaxiang Tan, Chengqi Gong, Guanghui Hou, Xiaoxiao Fang, Yang Yu, Moawiya Haddad, Marion Schindler, José Lopes Camilo Da Costa Alves, Junbin Fang, Xiangrong Yu, Kelvin Kam‐Lung Chong

“…Additionally, back propagation neural networks (BPNN) and universal network for image segmentation (U‐Net) were employed for image classification and segmentation of meibomian gland images to predict Demodex mite infections. …”
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Application of Convolutional Neural Networks in an Automatic Judgment System for Tooth Impaction Based on Dental Panoramic Radiography by Ya-Yun Huang, Yi-Cheng Mao, Tsung-Yi Chen, Chiung-An Chen, Shih-Lun Chen, Yu-Jui Huang, Chun-Han Chen, Jun-Kai Chen, Wei-Chen Tu, Patricia Angela R. Abu

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The feasibility of endoscopic stapes surgery: A three‐dimensional planning method by Maaike Jellema, Mijs Buter, Esther E. Blijleven, Koen Willemsen, H. Chien Nguyen, Robert J. Stokroos, Inge Wegner, Henricus G. X. M. Thomeer

“…Abstract Objective The primary aim of this study was to investigate the accuracy of a semi‐automatic algorithm in assessing the feasibility and complexity of endoscopic stapes surgery preoperatively. …”
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Abstract 045: A Radiomics Based Pipeline for Paired Risk‐Stratification of Intracranial Atherosclerotic Plaques by Elena S. Sagues Sese, Sebastian Sanchez, Sricharan Veeturi, Tatsat Patel, Vicent M. Tutino, Diego J. Ojeda, Jacob M. Miller, Arshaq Saleem, Andres Gudino, Bincheng Wang, Edgar A. Samaniego

“…Introduction High resolution vessel wall imaging (HR‐VWI) enables accurate visualization of intracranial atherosclerotic plaques. …”
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