Canadian Public Health Laboratory Network laboratory Guidelines for the Diagnosis of Neurosyphilis in Canada by Tom Wong, Kevin Fonseca, Max A Chernesky, Richard Garceau, Paul N Levett, Bouchra Serhir

“…Antibody assays include a VDRL assay and the FTA-Abs, while polymerase chain reaction for T. pallidum can be used as direct detection assays for some specimens. This chapter reviews guidelines for specimen types and sample collection, and identifies two possible algorithms for use with immunocompromised and immunocompetent hosts using currently available tests in Canada, along with a review of treatment response and laboratory testing follow-up.…”
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Advanced Deep Learning and Machine Learning Techniques for MRI Brain Tumor Analysis: A Review by Rim Missaoui, Wided Hechkel, Wajdi Saadaoui, Abdelhamid Helali, Marco Leo

“…In this study, we focus on current advances in medical imaging, particularly magnetic resonance imaging (MRI), and how machine learning (ML) and deep learning (DL) algorithms might be combined with clinical assessments to improve brain tumor diagnosis. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Comparative data suggest that while both machine learning and deep learning approaches perform well, some deep learning models may offer slight advantages in complex data environments. Advanced algorithms, including neural networks, decision trees, and random forests, significantly improved detection rates when integrated with EHRs, enabling real-time surveillance and timely interventions. …”
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Spatially Resolved River Monitoring by UAV-Borne 4D-Imaging Radar: Experiments and Preliminary Validation by Giordano Cicioni, Federico Alimenti, Timo Grebner, Julian Kanz, Ron Riekenbrauck, Christian Waldschmidt

“…We will first validate the sensor and algorithm in a controlled laboratory environment, and then deploy the system in various river environments, using both tripod-based and unmanned aerial vehicle (UAV)-based configurations. …”
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Automatic Extraction of Blood Vessels in the Retinal Vascular Tree Using Multiscale Medialness by Mariem Ben Abdallah, Jihene Malek, Ahmad Taher Azar, Philippe Montesinos, Hafedh Belmabrouk, Julio Esclarín Monreal, Karl Krissian

“…We propose an algorithm for vessel extraction in retinal images. …”
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Analysis of Electron Distribution Functions From the Magnetospheric Multiscale (MMS) Mission Using the Gaussian Mixture Model by Beniamino Sanò, Nathan N. Maes Anno, David L. Newman, Marty Goldman, Francesco Valentini, Denise Perrone, Giovanni Lapenta

“…The approach relies on a GMM algorithm to detect and characterize the number of distinct clusters within a VDF, and a model selection approach based on the Bayesian Information Criterion to determine the optimal number of clusters. …”
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High-Frequency-Based Transmission Line Percentage Differential Protection With Traveling Wave Alignment by Igor F. Prado, Flavio B. Costa, Kleber M. Silva, Rodrigo P. Medeiros, Bruce A. Mork

“…This paper presents a wavelet-based differential protection algorithm for transmission lines. It uses restraint and operating components obtained with high-frequency components of a few kHz from instantaneous energy values of the real-time boundary stationary wavelet transform instead of low-frequency components from phasor estimation. …”
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RETRACTED ARTICLE: Intelligent dynamic spectrum access using fuzzy logic in cognitive radio networks by K. Krishna Kishore, Arun Sekar Rajasekaran, Ismail Keshta, Haewon Byeon, Mohammed Wasim Bhatt, Azeem Irshad, Isaac Ofori

“…Fuzzy-based spectrum sensing algorithms allow for robust detection of spectrum opportunities by considering the “fuzziness” in the received signal strength and noise conditions.…”
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Epigenetic modifications of cfDNA in liquid biopsy for the cancer care continuum by Jodie Wong, Rohit Muralidhar, Liang Wang, Chiang-Ching Huang

“…It advocates for the integration of multi-omic data through machine learning algorithms to refine predictive models and stresses the importance of collaboration among clinicians, researchers, and data scientists. …”
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Bibliometric analysis and review of AI-based video generation: research dynamics and application trends (2020–2025) by Wei Xie, Anshu Hu, Qing Xie, Junjie Chen, Ruoyu Wan, Yuhan Liu

“…Our findings the rise of specific architectures, pinpoint high-activity application areas, reveal evolving thematic clusters, and also remarks persistent challenges, including technical hurdles and critical ethical issues such as deepfake detection, algorithmic transparency, and data privacy. …”
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Classification of mammograms: Comparing a graphical to a geometrical approach by Anirban Ghosh, Priya Ranjan, Kumar Dron Shrivastav, Rajiv Janardhanan

“…Radiologists often use mammography, a noninvasive and inexpensive imaging tool, for the detection and classification of breast cancer (BC) lesions. …”
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Nuevos modelos para la Caracterización, Detección y Diagnóstico de Fallas en Máquinas Eléctricas Rotativas by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…The main objective is to explore and propose new methodologies for characterizing faults in electric motors through the use of data analysis and machine learning techniques, reviewing traditional and current methods for fault diagnosis, including vibration analysis techniques and supervised and unsupervised learning algorithms. The potential of artificial intelligence algorithms to improve diagnosis and reduce subjectivity in data processing is also examined. …”
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Non-convex optimization with using positive-negative moment estimation and its application for skin cancer recognition with a neural network by P.A. Lyakhov, U.A. Lyakhova, R.I. Abdulkadirov

“…Multimodal neural network systems for analyzing heterogeneous dermatological data, using the proposed optimization algorithms, can be applied as a tool for auxiliary medical diagnostics, which will reduce the consumption of financial and labor resources involved in the medical industry, as well as increase the chance of early detection of pigmentary oncopathologies.…”
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Improved Key Microbial Biomarker Discovery Using Ensemble Statistical Methods by Walter Pirovano, Yashjit Gangopadhyay, Mirna Lilian Baak, Christiaan Arie de Leeuw, Radhika Bongoni, Eline Suzanne Klaassens

“…The framework integrates machine learning (ML) algorithms and statistical methods to determine the most relevant microbial biomarkers and signatures that explain variation in the microbial abundance counts and metadata classes based on predefined metrics. …”
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Multi-point estimation weldment recognition and estimation of pose with data-driven robotics design by Meng XiangYi

“…Concurrently, employing geometric hashing and iterative closest point algorithms enables precise pose estimation of the welding torch with an average error margin of less than 1 mm.…”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…The study highlights the potential of ML algorithms in early diabetes detection, enabling timely intervention and personalized management strategies. …”
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AI-Driven Wearable Bioelectronics in Digital Healthcare by Guangqi Huang, Xiaofeng Chen, Caizhi Liao

“…However, their widespread adoption faces technical, ethical, and regulatory hurdles, such as data interoperability, privacy concerns, algorithmic bias, and the need for robust clinical validation. …”
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Machine Learning and Artificial Intelligence Techniques in Smart Grids Stability Analysis: A Review by Arman Fathollahi

“…This work starts with a discussion of the smart grid’s dynamic structures and subsequently transitions into an overview of machine learning approaches that explore various algorithms and their applications to enhance smart grid operations. …”
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A Unified Denoising Framework for Restoring the LiDAR Point Cloud Geometry of Reflective Targets by Tianpeng Xie, Jingguo Zhu, Chunxiao Wang, Feng Li, Zhe Meng

“…LiDAR point clouds of reflective targets often contain significant noise, which severely impacts the feature extraction accuracy and performance of object detection algorithms. These challenges present substantial obstacles to point cloud processing and its applications. …”
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Precision Agriculture: Utilizing Machine Learning for Accurate Plant Disease Diagnosis by Divya Banti, Tandan Gajendra

“…Real time real data on crop conditions and stress factors is of great help to early detection of diseases through remote sensing. Mobile applications with ML algorithms also enable on the spot plant disease diagnosis from the smartphone camera, enabling site rather than later intervention. …”
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