Emerging biomarkers for early cancer detection and diagnosis: challenges, innovations, and clinical perspectives by Sameen Zafar, Amna Hafeez, Hania Shah, Iqra Mutiullah, Arslan Ali, Khushbukhat Khan, Gabriela Figueroa-González, Octavio Daniel Reyes-Hernández, Laura Itzel Quintas-Granados, Sheila I. Peña-Corona, Lashyn N. Kiyekbayeva, Monica Butnariu, Cristina-Elena Tota, Angela Caunii, Dietrich Büsselberg, Javad Sharifi-Rad, Gerardo Leyva-Gómez

“…Abstract Early detection and accurate cancer diagnosis are crucial for improving patient outcomes and survival rates. …”
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Anomaly detection solutions: The dynamic loss approach in VAE for manufacturing and IoT environment by Praveen Vijai, Bagavathi Sivakumar P

“…Anomaly detection is critical for enhancing operational efficiency, safety, and maintenance in industrial applications, particularly in the era of Industry 4.0 and IoT. …”
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Comparative analysis of automated foul detection in football using deep learning architectures by Abdallah Rabee, Zakaria Anwar, Ahmed AbdelMoety, Ahmed Abdelsallam, Mahmoud Ali

“…This study presents a comprehensive comparative evaluation of eight state-of-the-art Deep Learning (DL) architectures — EfficientNetV2, ResNet50, VGG16, Xception, InceptionV3, MobileNetV2, InceptionResNetV2, and DenseNet121 — applied to the task of automated foul detection in football. …”
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Fault Detection and Diagnosis in Industry 4.0: A Review on Challenges and Opportunities by Denis Leite, Emmanuel Andrade, Diego Rativa, Alexandre M. A. Maciel

“…Integrating Machine Learning (ML) in industrial settings has become a cornerstone of Industry 4.0, aiming to enhance production system reliability and efficiency through Real-Time Fault Detection and Diagnosis (RT-FDD). …”
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DFC-Net: Dual-Branch Collaborative Feature Enhancement for Cloud Detection in Remote Sensing Images by Wanting Zhou, Yan Mo, Qiaofeng Ou, Shaowei Bai

“…Although deep learning-based methods have achieved remarkable results, challenges remain in the fine-grained segmentation of cloud boundaries and the detection of thin clouds over complex land surfaces. …”
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RGB and RGNIR image dataset for machine learning in plastic waste detectionZENODO by Owen Tamin, Ervin Gubin Moung, Jamal Ahmad Dargham, Samsul Ariffin Abdul Karim, Ashraf Osman Ibrahim, Nada Adam, Hadia Abdelgader Osman

“…While spectral imaging offers a promising solution, it has several drawbacks, such as complexity, high cost, and limited spatial resolution. …”
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CASSAD: Chroma-Augmented Semi-Supervised Anomaly Detection for Conveyor Belt Idlers by Fahad Alharbi, Suhuai Luo, Abdullah Alsaedi, Sipei Zhao, Guang Yang

“…Idlers are essential to conveyor systems, as well as supporting and guiding belts to ensure production efficiency. Proper idler maintenance prevents failures, reduces downtime, cuts costs, and improves reliability. …”
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Heavy Equipment Detection on Construction Sites Using You Only Look Once (YOLO-Version 10) with Transformer Architectures by Ikchul Eum, Jaejun Kim, Seunghyeon Wang, Juhyung Kim

“…These findings underscore the method’s potential to strengthen on-site safety by providing more reliable and efficient heavy equipment detection in complex work environments, while also acknowledging areas for further refinement.…”
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Comprehensive fragmentation of cell-free repetitive DNA for enhanced cancer detection in plasma by Mingguang Zhang, Shuohui Dong, Wei Rao, Shiwen Mei, Gang Hu, Ling Liu, Zhen Wang, Jianqiang Tang

“…Five innovative repetitive fragmentomic features were designed: fragment ratio, fragment length, fragment distribution, fragment complexity, and fragment expansion. A machine learning-based multimodal model was developed using these features.ResultsThe multimodal model achieved high prediction performance for early tumor detection, even at ultra-low sequencing depths (0.1×, AUC = 0.9824). …”
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An In-Depth Comparative Study of Quantum-Classical Encoding Methods for Network Intrusion Detection by Adam Kadi, Aymene Selamnia, Zakaria Abou El Houda, Hajar Moudoud, Bouziane Brik, Lyes Khoukhi

“…In today’s rapidly evolving cyber landscape, the growing sophistication of attacks, including the rise of zero-day exploits, poses critical challenges for network intrusion detection. Traditional Intrusion Detection Systems (IDSs) often struggle with the complexity and high dimensionality of modern cyber threats. …”
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Terahertz all-silicon metasurfaces with off-axis bifocal characteristics for polarization detection by Li Hui, Duan Shouxin, Zheng Chenglong, Xu Hang, Li Jie, Song Chunyu, Yang Fan, Shi Wei, Zhang Yating, Shen Yun, Yao Jianquan

“…The combination between all-silicon metasurfaces and focused beams carrying polarization information has offered a new opportunity for miniaturized polarization detection behavior. Here, we investigate and experimentally demonstrate a new scheme for realizing efficiently miniaturized polarization detection behavior based on the polarization multiplexing encoding technique. …”
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A lightweight weed detection model for cotton fields based on an improved YOLOv8n by Jun Wang, Zhengyuan Qi, Yanlong Wang, Yanyang Liu

“…Abstract In modern agriculture, the proliferation of weeds in cotton fields poses a significant threat to the healthy growth and yield of crops. Therefore, efficient detection and control of cotton field weeds are of paramount importance. …”
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Two-Stage Target Detection for Compact HFSWR With Space-to-Depth YOLOv8 and Multiframe ViT by Tong Wu, Ming Li, Jiong Niu, Ling Zhang, Wandong Zhang, Qing Ming Jonathan Wu

“…These results confirm that MFTDF delivers superior detection accuracy and efficiency, offering a robust solution for maritime target detection in complex scenarios.…”
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RL-Net: a rapid and lightweight network for detecting tiny vehicle targets in remote sensing images by Yaoyao Du, Li Chen, Xingxing Hao

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Fibrin monomer complex on postoperative day 1 is correlated with the volume of deep vein thrombosis after knee surgery by Manabu Akagawa, Hiroaki Kijima, Yoshiaki Kimura, Hidetomo Saito, Kimio Saito, Ikuko Wakabayashi, Takeshi Kashiwagura, Naohisa Miyakoshi

“…It has not been identified how to efficiently detect high‐risk DVT while minimizing bleeding complications from anticoagulation. …”
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YOLO-Act: Unified Spatiotemporal Detection of Human Actions Across Multi-Frame Sequences by Nada Alzahrani, Ouiem Bchir, Mohamed Maher Ben Ismail

“…This paper introduces YOLO-Act, a novel spatiotemporal action detection model that enhances the object detection capabilities of YOLOv8 to efficiently manage complex action dynamics within video sequences. …”
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Insertion/deletion polymorphisms in the ΔNp63 promoter are a risk factor for bladder exstrophy epispadias complex. by Simon Wilkins, Ke Wei Zhang, Istiak Mahfuz, Renaud Quantin, Nancy D'Cruz, John Hutson, Michael Ee, Darius Bagli, Karen Aitken, Fion Nga-Yin Fong, Patrick Kwok-Shing Ng, Stephen Kwok-Wing Tsui, Wendy Yin-Wan Fung, Tahmina Banu, Atul Thakre, Kaid Johar, Enrique Jaureguizar, Long Li, Wei Cheng

“…Bladder exstrophy epispadias complex (BEEC) is a severe congenital anomaly; however, the genetic and molecular mechanisms underlying the formation of BEEC remain unclear. …”
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A lightweight and optimized deep learning model for detecting banana bunches and stalks in autonomous harvesting vehicles by Duc Tai Nguyen, Phuoc Bao Long Do, Doan Dang Khoa Nguyen, Wei-Chih Lin

“…Notably, the proposed model outperforms the previous detection models, offering high accuracy while optimizing computational efficiency. …”
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RLita: A Region-Level Image–Text Alignment Method for Remote Sensing Foundation Model by Qiang Zhang, Decheng Wang, Xiao Yu

“…Experiments on five remote sensing datasets including object detection, semantic segmentation, and change detection show the effectiveness of the RLita method.…”
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Criminal emotion detection framework using convolutional neural network for public safety by Jay Raval, Nilesh Kumar Jadav, Sudeep Tanwar, Giovanni Pau, Fayez Alqahtani, Amr Tolba

“…The proposed framework is evaluated with different evaluation metrics, such as training accuracy, loss, optimizer performance, precision-recall curve, model complexity, training time, and inference time. In crime detection, the CNN model achieves a remarkable accuracy of 92.45% and in criminal emotion detection, LeNet-5 outperforms other CNN architectures by offering an accuracy of 98.6%.…”
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