A Comprehensive Investigation of Anomaly Detection Methods in Deep Learning and Machine Learning: 2019–2023 by Shalini Kumari, Chander Prabha, Asif Karim, Md. Mehedi Hassan, Sami Azam

“…Almost 85% of companies polled said they were looking into anomaly detection (AD) technologies for their industrial image anomalies. …”
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T2*-weighted imaging for detection of intracranial silicone oil in MRI obtained with motion correction sequences by Ryuta Yasuda, Masayuki Maeda, Kenichi Takada, Katsuhiro Inoue, Masataka Sugao, Hidenori Suzuki

“…MRI was performed with MultiVane XD due to the significant patient’s restlessness, and among all sequences including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), fluid-attenuated inversion recovery (FLAIR) and T2*WI, only T2*WI detected intracranial silicone oil. In contrast, another MRI obtained previously with conventional turbo spin-echo detected intracranial silicone oil not only in T2*WI but also in T1WI, T2WI and FLAIR. …”
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Efficient Handling of Data Imbalance in Health Insurance Fraud Detection Using Meta-Reinforcement Learning by Supriya Seshagiri, K. V. Prema

“…Data imbalance is one of the major challenges in health insurance fraud detection where the distribution of classes within the dataset is significantly skewed, leading statistical models to be biased toward the dominant class. …”
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Diagnostic Performance of Deep Learning Applications in Hepatocellular Carcinoma Detection Using Computed Tomography Imaging by Enes Şahin, Ozan Can Tatar, Mehmet Eşref Ulutaş, Sertaç Ata Güler, Turgay Şimşek, Nihat Zafer Utkan, Nuh Zafer Cantürk

“…Background/Aims: Hepatocellular carcinoma (HCC) is a prevalent cancer that significantly contributes to mortality globally, primarily due to its late diagnosis. Early detection is crucial yet challenging. This study leverages the potential of deep learning (DL) technologies, employing the You Only Look Once (YOLO) architecture, to enhance the detection of HCC in computed tomography (CT) images, aiming to improve early diagnosis and thereby patient outcomes. …”
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A conceptual approach to material detection based on damping vibration-force signals via robot by Ahmad Saleh Asheghabadi, Mohammad Keymanesh, Saeed Bahrami Moqadam, Saeed Bahrami Moqadam, Saeed Bahrami Moqadam, Jing Xu

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Large deflections of agglomerated carbon nanotubes reinforced sandwich cantilever beam partially embedded on foundation by Bui, Thi Thu Hoai, Tran, Thi Thu Huong, Pham, Vu Nam, Nguyen, Dinh Kien 

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The Discernment of the Deceits of the Devil in angelum lucis according to St. Ignatius of Loyola and St. John of the Cross by Juan Manuel Rossi

“…In this field, because of its particular difficulty, special attention should be paid to the deceptions of the devil “sub angelo lucis”, that is, those who are under the appearance of good or virtue. …”
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Detection of Mycobacterium avium subsp. paratuberculosis and other mycobacteria in retail milk and dairy products in Argentina by Karina Cirone, C. Morsella, L. Mendez, F. Paolicchi

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Oklopno vozilo - topovljača na točkovima 'COMMANDO V-600', International defense review, 1989 by M.P.

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DIAGNOSTIC ACCURACY OF CONTRAST–ENHANCED HIGHRESOLUTION MAGNETIC RESONANCE IMAGING (MRI) FORTHE DETECTION OF RETINOBLASTOMA by Muhammad Faisal

“… Objective To determine the diagnostic accuracy of contrast–enhanced high resolution magnetic resonance imaging (MRI) in the detection of retinoblastoma taking histopathology as the gold standard. …”
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Comparison of saliva and blood derived cell free RNAs for detecting oral squamous cell carcinoma by Yuan Hu, Manbin Xu, Muyuan Liu, Hanwei Peng

“…In our study to enhance OSCC detection, we analyzed cell-free RNA (cfRNA) transcriptomes (mRNA, lncRNA) from blood (plasma) and saliva samples of individuals in three groups: OSCC group, oral benign tumor group, and a normal control group. …”
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Capsule neural network and adapted golden search optimizer based forest fire and smoke detection by Luling Liu, Li Chen, Mehdi Asadi

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The emerging role of blood-based biomarkers in early detection of colorectal cancer: A systematic review by Faris Shweikeh, Yuhao Zeng, Abdur Rahman Jabir, Erica Whittenberger, Saurav P. Kadatane, Yuting Huang, Mohamad Mouchli, Dani Ran Castillo

“…Background: Colorectal cancer (CRC), the third most commonly diagnosed and second most lethal cancer worldwide, necessitates efficient early detection strategies to improve patient outcomes. This review evaluates the promise of novel blood-based biomarkers for early detection of CRC. …”
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Recommendations for the Detection and Mitigation of Laurel Wilt Disease in Avocado and Related Tree Species in the Home Landscape by Jonathan Henry Crane, Jeff Wasielweski, Daniel Carrillo, Romina Gazis, Bruce Schaffer, Fredy Ballen, Edward Evans

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Construction of a pathogenic microorganism detection method based on third-generation nanopore sequencing data by Guoqin Mai, Jiayi Chen, Min Zhang, Wanyue Zhang, Yuting Luo, Ying Dai

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Detecting second mesiobuccal canal in maxillary first molars in Erbil citizens: CBCT Retrospective study. by Mustafa T. Mohamadamin, Karam A. Thiab, Ribwar F. Khalid, Khidir M. Khidir

“…These results indicate that CBCT is an effective, high-precision diagnostic tool for detecting canals. …”
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Mape: defending against transferable adversarial attacks using multi-source adversarial perturbations elimination by Xinlei Liu, Jichao Xie, Tao Hu, Peng Yi, Yuxiang Hu, Shumin Huo, Zhen Zhang

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Swarm learning with weak supervision enables automatic breast cancer detection in magnetic resonance imaging by Oliver Lester Saldanha, Jiefu Zhu, Gustav Müller-Franzes, Zunamys I. Carrero, Nicholas R. Payne, Lorena Escudero Sánchez, Paul Christophe Varoutas, Sreenath Kyathanahally, Narmin Ghaffari Laleh, Kevin Pfeiffer, Marta Ligero, Jakob Behner, Kamarul A. Abdullah, Georgios Apostolakos, Chrysafoula Kolofousi, Antri Kleanthous, Michail Kalogeropoulos, Cristina Rossi, Sylwia Nowakowska, Alexandra Athanasiou, Raquel Perez-Lopez, Ritse Mann, Wouter Veldhuis, Julia Camps, Volkmar Schulz, Markus Wenzel, Sergey Morozov, Alexander Ciritsis, Christiane Kuhl, Fiona J. Gilbert, Daniel Truhn, Jakob Nikolas Kather

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Leveraging time-based spectral data from UAV imagery for enhanced detection of broomrape in sunflower by Guy Atsmon, Anna Brook, Tom Avikasis Cohen, Fadi Kizel, Hanan Eizenberg, Ran Nisim Lati

“…Results showed that the PRNN model, trained on time-series data, achieved an overall accuracy of 84.8 % and a true positive rate of 80.4 % in detecting broomrape infection, emphasizing the strength of utilizing temporal data for enhancing detection accuracies. …”
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Detecting Subtle Shifts: Comparing SME Performance Drivers Pre and During the Covid-19 Pandemic by Soza Sydney Simango, Helper Zhou

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