Detection of possible aminoglycosides resistance mechanisms in Pseudomonas aeruginosa resistant isolates by Maria R. Boushra, Noha A. Hassuna, Gamal F.M. Gad, Reham A. Ibrahem, Nancy G.F.M. Waly

“…This study aimed to determine the resistance patterns to several antibiotics as well as the possible mechanisms of aminoglycosides resistance, including aminoglycosides modifying enzymes (AMEs), genes, and active efflux system, observed in clinical P. aeruginosa isolates recovered from patients admitted to Minia University Hospitals, Minia, Egypt. …”
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An optimized ensemble model with advanced feature selection for network intrusion detection by Afaq Ahmed, Muhammad Asim, Irshad Ullah, Zainulabidin, Abdelhamied A. Ateya

“…However, these methods often fall short in detecting sophisticated and evolving threats, particularly those involving subtle variations or mutations of known attack patterns. …”
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A machine learning model for early detection of sexually transmitted infections by Juma Shija, Judith Leo, Elizabeth Mkoba

“…Also, it can provide insights into infection patterns, allowing practitioners to adapt their responses. …”
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Acoustic Detection and Quantification of Fish in Lancang Waters of Seribu Islands, Indonesia by Syahrul Purnawan, Henry M. Manik, Agustina Sartika Manik, La Elson, Myounghee Kang

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Lightweight and hybrid transformer-based solution for quick and reliable deepfake detection by Geeta Rani, Atharv Kothekar, Shawn George Philip, Vijaypal Singh Dhaka, Ester Zumpano, Ester Zumpano, Eugenio Vocaturo, Eugenio Vocaturo

“…Moreover, it utilizes the unique features of transformer and Linformer models to enhance the robustness and generalization of deepfake detection techniques. The low computational requirement and high accuracy of 98.9% increase the real-time applicability of the model, preventing blackmail and other losses to the public.DiscussionThe proposed hybrid model utilizes the strength of the transformer model in capturing complex patterns in data. …”
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Detection of Banana Diseases Based on Landsat-8 Data and Machine Learning by Renata Retkute, Kathleen S. Crew, John E. Thomas, Christopher A. Gilligan

“…For TR4 in Mozambique, the approach successfully tracked disease progression, revealing clear spatial spread patterns and correlations as high as 0.98 between VI anomalies and disease cases in some pixels. …”
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Efficient Anomaly Detection for Edge Clouds: Mitigating Data and Resource Constraints by Javad Forough, Hamed Haddadi, Monowar Bhuyan, Erik Elmroth

“…Our approach exploits transfer learning by utilizing knowledge from a pre-trained model and adapting it for anomaly detection on edge clouds. This enables the model to benefit from the learned features and patterns from related tasks such as network intrusion detection, resulting in improved detection accuracy. …”
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Enhancing Retail Strategies Through Anomaly Detection in Association Rule Mining by Bijayini Mohanty, Santi Lata Champati, Swadhin Kumar Barisal

“…Association rule mining (ARM) is a fundamental technique for uncovering meaningful patterns and relationships within retail datasets, providing valuable insights for decision-making processes in the retail industry. …”
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Universal PCR assays to detect Candida FKS and ERG11 mutations by Dr Yuk Yam Cheung, Mr. Zhi Hao ZHANG, Ms. Wing Yan CHAR, Mr. Tsun Hang FONG, Mr. Chun Yu LI

“…For patients infected with Candida carrying FKS and/or ERG11 mutations, alternative treatment options may be necessary, underscoring the importance of rapid and accurate diagnostic tools for the detection of the mutations. Moreover, the developed assays can facilitate ongoing surveillance of antifungal resistance patterns in clinical isolates as the resistance landscape continues to evolve. …”
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Analysis of differential gene expression of PBMC for the in vitro detection of drug sensitization by Andreas Glässner, Michael Steffens, Amol Fatangare, Gerda Wurpts, Per Hoffmann, Philipp N. Deck, Christine Krämer, Stefani Röseler, Albert Sickmann, Markus M. Nöthen, Amir S. Yazdi, Bernhardt Sachs

“…Background: The detection of drug-specific activation of T cells in the lymphocyte transformation test (LTT) is mainly based on cell proliferation or cytokine secretion. …”
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Early detection of retinal and choroidal microvascular impairments in diabetic patients with myopia by Yufei Wu, Yufei Wu, Jiahui Jiang, Xiaoyu Deng, Xixi Zhang, Jinger Lu, Zian Xu, Yitian Zhao, Zai-Long Chi, Zai-Long Chi, Qinkang Lu, Qinkang Lu

“…A ResNet-50 convolutional neural network was further applied to analyze vascular density patterns and assist in DR grading. Univariate and multiple linear regression analyses explored the associations between perfusion and risk factors.ResultsThe inner ring retinal vessel density and CVI in all areas were significantly different between groups (P < 0.05); CPV was not significantly changed except for the inferotemporal area among the groups. …”
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Advanced strategy for cancer detection based on volatile organic compounds in breath by Ziqi Jia, Yiwen Jiang, Tongxuan Shang, Heng Cao, Jiayi Li, Lin Cong, Pengming Pu, Hengyi Xu, Yuchen Liu, Yansong Huang, Dongxu Ma, Jiang Wu, Ruijie Zhou, Xiang Wang, Chang bao Han, Jiaqi Liu

“…Two primary methodologies are employed for VOCs detection: mass spectrometry (MS)-based techniques, which provide high-precision identification and quantification of individual compounds, and sensor-based pattern recognition methods, which detect disease-specific VOC signatures. …”
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Automatic detection of lucky bamboo nodes based on Improved YOLOv7 by Jing Zhang, Jing Zhang, Jing Zhang, Ruoling Deng, Ruoling Deng, Ruoling Deng, Chengzhi Cai, Erpeng Zou, Haitao Liu, Haitao Liu, Mingxin Hou, Xinzhi Chen, Huamin Lin, Zhenye Wei

“…Future work will address limitations in detecting nodes obscured by mottled patterns or severe occlusions by expanding label categories during training.…”
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Outpatient acute kidney disease detection by national and institutional health data by Hsiu-Yin Chiang, Hung-Chieh Yeh, Zi-Han Lin, Bradley Chen, David Ray Chang, I-Wen Ting, Jie-Sian Wang, Yun-Lun Chang, Hung-Lin Chen, Yu-Chih Liu, Mei-Chuan Hsieh, Tzu-Ling Karen Tzeng, Chin-Chi Kuo

“…Conclusions By integrating the national-local data using the AKIDS, this study comprehensively characterizes a previously unrecognized phenotype, AKDOPT, illustrating the potential of healthcare big data in transforming global approaches to AKD patterns and prevention.…”
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Rolling window for detecting multiple Chan signatures to diagnose excessive water production by Ahmed MohamedSalih Musa Hamdoon, A. P. Mohammed Abdalla Ayoub Mohammed, A. P. Khaled Abdalla Elraies

“…While machine learning models were developed to automate Chan plot interpretation and reduce human bias, they often failed to capture the evolution of water production over time, typically detecting only a single pattern or capturing patterns after it fully materialized, reducing the chance of early diagnosing. …”
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Temporal Heterogeneous Graph Contrastive Learning for Fraud Detection in Credit Card Transactions by Jiyuan Wang, Jingyi Liu, Wenxia Zheng, Yao Ge

“…Credit card fraud detection remains a critical challenge in financial security, characterized by evolving fraud patterns, sparse labeled data, and severe class imbalance. …”
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Performance Assessment of the Concepta Automated ANA Detection System in Routine Clinical Samples by Kübra Evren, Ayşe Nur Ceylan, Mehmet Akif Durmuş

“…Aim: Indirect immunofluorescence (IIF) on HEp-2 cells is the standard method for detecting anti-nuclear antibodies (ANA) due to its high sensitivity. …”
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Guest Editorial: Anomaly detection and open‐set recognition applications for computer vision by Hakan Cevikalp, Robi Polikar, Ömer Nezih Gerek, Songcan Chen, Chuanxing Geng

“…Abstract Anomaly detection is a method employed to identify data points or patterns that significantly deviate from expected or normal behaviour within a dataset. …”
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IRFNet: Cognitive-Inspired Iterative Refinement Fusion Network for Camouflaged Object Detection by Guohan Li, Jingxin Wang, Jianming Wei, Zhengyi Xu

“…Camouflaged Object Detection (COD) aims to identify objects that are intentionally concealed within their surroundings through appearance, texture, or pattern adaptations. …”
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Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations by Phuc Hao do, Tran Duc Le, Truong Duy Dinh, van Dai Pham

“…The Original-KAN variant, in particular, excelled in capturing complex, non-linear patterns inherent in IoT botnet traffic, achieving higher accuracy and faster convergence rates. …”
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