Incidental Thoracic Th1 Spina Bifida Occulta Detection Following Sports Injury: A Case Report with Comprehensive Radiological Insights by Sinan Kara, Amel Gorani, Bruno Baillon, Alexandre Grandjean, Thomas Von Waldburg, Tevi Morel Lawson

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Accuracy of the Modified Finnish Diabetes Risk Score (Modified FINDRISC) for detecting metabolic syndrome: Findings from the Indonesian national health survey. by Indriastuti Cahyaningsih, M Rifqi Rokhman, Sudikno, Maarten J Postma, Jurjen van der Schans

“…<h4>Conclusion</h4>Metabolic syndrome is prevalent in Indonesia, and the Modified FINDRISC tool offers good diagnostic accuracy for detecting such cases. Utilising Modified FINDRISC as a first-instance screening modality will reduce the number of people requiring further confirmation tests. …”
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YOLOv8-SDC: An Improved YOLOv8n-Seg-Based Method for Grafting Feature Detection and Segmentation in Melon Rootstock Seedlings by Lixia Li, Kejian Gong, Zhihao Wang, Tingna Pan, Kai Jiang

“…The experimental results show that YOLOv8-SDC achieves significant accuracy improvements over the original YOLOv8n-seg model, YOLACT, Mask R-CNN, YOLOv5, and YOLOv11 in both object detection and instance segmentation tasks under top-view and side-view conditions. …”
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An Application of Deep Learning Models for the Detection of Cocoa Pods at Different Ripening Stages: An Approach with Faster R-CNN and Mask R-CNN by Juan Felipe Restrepo-Arias, María José Montoya-Castaño, María Fernanda Moreno-De La Espriella, John W. Branch-Bedoya

“…Results showed that YOLOv8x achieved the highest mAP of 86.36%, outperforming YOLOv8l-seg (83.85%), Mask R-CNN (73.20%), and Faster R-CNN (67.75%) in overall detection accuracy. However, the R-CNN models offered valuable instance-level segmentation insights, particularly in complex backgrounds. …”
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Revolutionary advances in nanomaterials-based electrochemical biosensors for precise cancer biomarker analysis by Fatima Yaseen, Muhammad Hashim Khan, Shahaab Jilani, Ali Turab Jafry, Asim Yaqub, Huma Ajab

“…Within this assessment, various electrochemical detection techniques for cancer biomarkers are outlined, encompassing illustrative instances showing the benefits of electrochemical sensors customized with a range of nanomaterials (NMs). …”
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Accurately Identifying Different Ripening Stages of Strawberry Fruits in Complex Agricultural Scenarios by Xuefeng Ren, Yang Gan, Huan Liu, Yongming Chen, Ping Lin

“…Finally, the model’s effectiveness in detecting strawberries at different ripening stages is validated on a large-scale dataset containing over 90,000 instances. …”
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Preliminary evaluation of a neurological clinical pathway for the early detection of leprosy in low-endemic settings: A single-center exploratory study by Xiaohua Chen

“…Common misdiagnoses included peripheral neuropathy (29 instances) and skin lesions (13 instances). The neurological CP implemented in this study has potential utility for early leprosy detection in low-endemic settings. …”
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Targeted next-generation sequencing enhances precision and rapid detection in healthcare-associated infection Surveillance: Unveiling multidrug-resistant colonization in ICUs by Tangchun Liu, Shuyan Deng, Wandi Liu, Jinzhao Zhang, Pengfei Wang, Zhengfei Yang

“…Results: In 23 nasal swab samples from EICU group, tNGS detected 14 species of microorganism in 29 instances within 19 h. …”
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Enhancing anomaly detection in IoT-driven factories using Logistic Boosting, Random Forest, and SVM: A comparative machine learning approach by Mohammed Aly, Mohamed H. Behiry

“…Abstract Three machine learning algorithms—Logistic Boosting, Random Forest, and Support Vector Machines (SVM)—were evaluated for anomaly detection in IoT-driven industrial environments. A real-world dataset of 15,000 instances from factory sensors was analyzed using ROC curves, confusion matrices, and standard metrics. …”
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Research on Damage Detection of Dual-Rotor Synchronous Excitation Mine Screen Beams Based on Strain Mode Difference Vibration Mode Analysis by Xiaohao Li, Yahui Wang, Yang Zhou

“…The feasibility and validity of the engineering application of the concept are demonstrated through instances.…”
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A novel univariate feature selection with ANOVA F-test-based machine learning model for Intrusion Detection Framework of Robotics system by Narinder Verma, Neerendra Kumar, Kuljeet Singh, Abeer Aljohani, Anurag Sinha, Syed Abid Hussain

“…However, increasing the integration of robotic systems into critical infrastructures exposes devices to cybersecurity threats. The intrusion detection system (IDS) plays a vital role in safeguarding the systems from malicious activities and unauthorized access. …”
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ShipRSImageNet: A Large-Scale Fine-Grained Dataset for Ship Detection in High-Resolution Optical Remote Sensing Images by Zhengning Zhang, Lin Zhang, Yue Wang, Pengming Feng, Ran He

“…Ship detection in optical remote sensing images has potential applications in national maritime security, fishing, and defense. …”
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QCAE-QOC-SVM: A hybrid quantum machine learning model for DoS and Fuzzy attack detection on autonomous vehicle CAN bus by Meghana R, Sowmyashree Sakrepatna Ramesha, Adwitiya Mukhopadhyay

“…The method effectively extracts patterns from CAN bus traffic with the help of quantum-powered classification for accurate anomaly detection. The model was assessed using a public and custom dataset of 300,000 instances generated through the CARLA simulator and was run on a high-performance computing facility. …”
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Machine learning classifiers to detect data pattern change of continuous emission monitoring system: A typical chemical industrial park as an example by Zhefeng Xu, Xiahong Shi, Wei Shu, Yilu Xin, Xuan Zan, Zhaonian Si, Jinping Cheng

“…Temporal emission pattern analysis revealed significant changes in 334 instances (90% confidence) across collection weeks, though only 24 aligned with regulatory offsite supervision records, highlighting discrepancies between algorithmic detection and traditional compliance checks. …”
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Detecting circulating microbial cell-free DNA by next-generation sequencing in patients with Mycobacterium avium complex-lung disease: A pilot study by Yen-Han Tseng, Sheng-Wei Pan, Jia-Yih Feng, Wei-Juin Su, Chi-Ying F Huang, Yuh-Min Chen

“…Results: Two (40%) plasma samples from MAC-LD patients had detectable MAC-specific cfDNA, namely one instance of DNA polymerase III alpha subunit and one instance of ATP-binding cassette transporters permease. …”
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Multi-body sensor based drowsiness detection using convolutional programmed transfer VGG-16 neural network with automatic driving mode conversion by Meenakshi Malik, Preeti Sharma, Gurpreet Kaur Punj, Supreet Singh, Fikreselam Gared

“…This study suggests a novel method for machine learning-based automatic driving change-based drowsiness detection. In this instance, the multi-body sensor detects the driver’s EEG signal and gathers information for brain activity analysis. …”
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Epidemiological changes in Chlamydia pneumoniae molecular detections before, during and after the COVID-19 pandemic in 27 European sites and Taiwan, 2018 to 2023 by on behalf of the ESCMID Study Group for Mycoplasma and Chlamydia infections (ESGMAC)

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On the way to eco-friendly fabrication of polyaniline-based ammonia sensors with high sensitivity and room temperature operation by Sabine Vassaux, Nathalie Redon, Caroline Duc

“…For instance, high sensitivities (about 300 %/ppm) and low limits of detection (approximately 2 ppb) are obtained for devices elaborated in ethanol and dl-limonene. …”
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A Monocular Vision-Based Safety Monitoring Framework for Offshore Infrastructures Utilizing Grounded SAM by Sijie Xia, Rufu Qin, Yang Lu, Lianjiang Ma, Zhenghu Liu

“…By combining advanced computer vision techniques such as Grounded SAM and horizon-based self-calibration, the proposed framework achieves accurate vessel detection, instance segmentation, and distance estimation. …”
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A convolutional autoencoder framework for ECG signal analysis by Ugo Lomoio, Patrizia Vizza, Raffaele Giancotti, Salvatore Petrolo, Sergio Flesca, Fabiola Boccuto, Pietro Hiram Guzzi, Pierangelo Veltri, Giuseppe Tradigo

“…The results show interesting results in automatic anomaly detection to support physicians in the decision process. …”
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