Early detection of bacterial pneumonia by characteristic induced odor signatures by Kim Arnold, Alejandro Gómez-Mejia, Miguel de Figueiredo, Julien Boccard, Kapil Dev Singh, Serge Rudaz, Pablo Sinues, Annelies S. Zinkernagel

“…Results Characteristic changes in the VOCs emitted from the mice were detected as early as 4–6 h post-inoculation. Additionally, by using each mouse as its own baseline, we mimicked the inherent variation within biological organism and reported significant variations in 25 volatile organic compounds (VOCs) during the course of a lung bacterial infection. …”
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A Lightweight Citrus Object Detection Method in Complex Environments by Qiurong Lv, Fuchun Sun, Yuechao Bian, Haorong Wu, Xiaoxiao Li, Xin Li, Jie Zhou

“…Experimental results indicate that for the citrus dataset collected in a natural environment, the improved model reduces Params and GFLOPs by 15.4% and 23.7%, respectively, while improving precision, recall, and mAP by 0.3%, 4%, and 3.5%, respectively, thereby outperforming other detection networks. Additionally, an analysis of citrus object detection under varying lighting and occlusion conditions reveals that the YOLO-PBGM network model demonstrates good adaptability, effectively coping with variations in lighting and occlusions while exhibiting high robustness. …”
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From Conjugation to Detection: Development of Lateral Flow Assay for Zearalenone by Vinayak Sharma, Bilal Javed, Hugh J. Byrne, Furong Tian

“…The development of rapid, sensitive and cost-effective lateral flow assays is crucial for the detection of mycotoxins, ideally at the point-of-care level. …”
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Detecting Keratoconus in Adolescents with Anterior Segment Optical Coherence Tomography by Burcu Yücekul, Anika Förster, H. Burkhard Dick, Suphi Taneri

“…Assessing the applicability of an algorithm developed for keratoconus detection in adolescents. This algorithm relies on optical coherence tomography (OCT) and incorporates features related to corneal pachymetric and epithelial thickness alterations. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…We enhance the model’s diagnostic capability through complex image preprocessing techniques, such as improved noise reduction and morphological approaches. Additionally, we use Otsu’s thresholding method to segment blood vessels accurately. …”
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Bitemporal Remote Sensing Change Detection With State-Space Models by Lukun Wang, Qihang Sun, Jiaming Pei, Muhammad Attique Khan, Maryam M. Al Dabel, Yasser D. Al-Otaibi, Ali Kashif Bashir

“…However, much of the research focuses on improving global modeling, neglecting the role of local information crucial for change detection. Moreover, there remains a gap in understanding which structural modifications are more suited for the change detection task. …”
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Optimizing micro cold storage for detecting stale food and fruits by Arun Sreelekha, Amit Wagle Shivali, Nambiar Prahas, Panalkar Pratham, Ekka Prince, Kumar Vaibhav, Dhiman Harsh, Roy Anindita

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Adversarial domain adaptation for deforestation detection in remote sensing imagery by José Matheus Fonseca dos Santos, Pedro Juan Soto Vega, Guilherme Lucio Abelha Mota, Gilson Alexandre Ostwald Pedro da Costa

“…Alike other remote sensing applications, deforestation detection tends to present a poor accuracy when evaluated in a cross-domain scenario. …”
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Multimodal Siamese networks for dementia detection from speech in women by Amel Ksibi, Ahlem Walha, Mohammed Zakariah, Manel Ayadi, Tagrid Alshalali, Nouf Abdullah Almujally

“…Abstract The critical need for early and precise detection of dementia, a crippling cognitive illness that primarily affects women, is addressed by this study. …”
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Machine learning-assisted image analysis techniques for glaucoma detection by Vaibhav Yadav, Barnali Dey, Udayan Baruah, Saumya Das, Om Prakash

“…The discussed methodologies are further evaluated in terms of performance parameters, such as accuracy, sensitivity, specificity, and area under the curve. In addition, this research demonstrates hybrid methodologies for glaucoma detection and their advantages over machine learning and deep learning approaches. …”
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360 Using machine learning to analyze voice and detect aspiration by Cyril Varghese, Jianwei Zhang, Sara A. Charney, Abdelmohaymin Abdalla, Stacy Holyfield, Adam Brown, Hunter Stearns, Michelle Higgins, Julie Liss, Nan Zhang, David G. Lott, Victor E. Ortega, Visar Berisha

“…Supervised machine learning using five folds cross-validated neural additive network modelling (NAM) was performed on the phonations of aspirator versus non-aspirators. …”
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Exploring Transformer-Based Learning for Negation Detection in Biomedical Texts by Ghadeer Althari, Mohammad Alsulmi

“….), as every visit to the hospital leads to the addition of more information to the patient’s record. …”
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DVCW-YOLO for Printed Circuit Board Surface Defect Detection by Pei Shi, Yuyang Zhang, Yunqin Cao, Jiadong Sun, Deji Chen, Liang Kuang

“…However, current approaches to PCB defect detection face challenges, including large model sizes and difficulties in balancing detection accuracy with speed. …”
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Development of molecularly imprinted polymers for the detection of human chorionic gonadotropin by Radvilė Zubrytė, Liliia Mavliutova, Yadiris García, Mark V. Sullivan, Nicholas W. Turner, Francesco Patitucci, Laura C. Polania, Verónica A. Jiménez, Robert Porter, Alice Mattsson, Börje Sellergren

“…Here, we report the development of MIP nanogels for hCG detection, exploiting epitopes and magnetic templates for high-yielding dispersed phase imprinting. …”
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GenAI-Based Models for NGSO Satellites Interference Detection by Almoatssimbillah Saifaldawla, Flor Ortiz, Eva Lagunas, Abuzar B. M. Adam, Symeon Chatzinotas

“…Recent advancements in satellite communications have highlighted the challenge of interference detection, especially with the new generation of non-geostationary orbit satellites (NGSOs) that share the same frequency bands as legacy geostationary orbit satellites (GSOs). …”
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Dielectrophoresis-based microfluidics for detection and separation of circulating tumor cells by Iman Najafipour, Pegah Sadeh, Ali Mohammad Amani, Hesam Kamyab, Shreeshivadasan Chelliapan, Saravanan Rajendran, Ana Belén Peñaherrera-Pazmiño, Sajad Jamalpour

“…Circulating tumor cells (CTCs) represent a critical focus in cancer research due to their potential to enable early detection, monitor disease progression, and facilitate personalized therapies. …”
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Classification of and detection techniques for RNAi-induced effects in GM plants by Cecilia Diaz, Steve U. Ayobahan, Samson Simon, Luise Zühl, Andreas Schiermeyer, Elke Eilebrecht, Sebastian Eilebrecht

“…This review aims to classify mechanisms of RNAi effects induced by short interfering RNA from different sources in plants and to identify technologies that can be used to detect these effects. In addition, practical case studies are summarized and discussed in which previously unintended RNAi effects in genetically modified plants have been investigated. …”
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SHAZAM: Self-Supervised Change Monitoring for Hazard Detection and Mapping by Samuel Garske, Konrad Heidler, Bradley Evans, Kee Choon Wong, Xiao Xiang Zhu

“…SHAZAM offers an effective and generalisable solution for hazard detection and mapping across different geographical regions and a diverse range of hazards, and highlights the potential of further self-supervised method contributions for hazard detection and mapping.…”
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Exploration of machine learning approaches for automated crop disease detection by Annu Singla, Ashima Nehra, Kamaldeep Joshi, Ajit Kumar, Narendra Tuteja, Rajeev K. Varshney, Sarvajeet Singh Gill, Ritu Gill

“…Recent advancements in machine learning (ML) offer promising alternatives by automating the disease detection processes with high precision and efficiency. …”
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Advances in the Detection and Identification of Bacterial Biofilms Through NIR Spectroscopy by Cristina Allende-Prieto, Lucía Fernández, Pablo Rodríguez-Gonzálvez, Pilar García, Ana Rodríguez, Carmen Recondo, Beatriz Martínez

“…These results demonstrate that this technique is effective and reliable, indicating great potential for its application in the field of biofilm detection.…”
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