Implementing comprehensive geriatric assessment in an academic hematologic outpatient setting: experiences from medical doctors and patients by Steven Pierre Hiltgen, Heike A. Bischoff-Ferrari, Heike A. Bischoff-Ferrari, Michael Gagesch, Michael Gagesch, Michael Gagesch, Alexander Kaltenborn, Markus G. Manz, Max J. Rieger, Rahel Schwotzer, Sebastian M. Stolz, Thorsten Zenz, Wiebke Rösler

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Prediction models for Mtb infection among adolescent and adult household contacts in high tuberculosis incidence settings. by Edson Tawanda Marambire, Claire J Calderwood, Leyla Larsson, Kathrin Held, Palwasha Khan, Denise Banze, Celina Nhamuave, Lillian T Minja, Alfred Mfinanga, Rishi K Gupta, Celso Khosa, Junior Mutsvangwa, Norbert Heinrich, Katharina Kranzer

“…Tuberculosis preventive therapy (TPT) is highly effective, but implementation is hindered by limited accessibility of diagnostic tests aimed at detecting Mycobacterium tuberculosis (Mtb) infection. …”
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Intravitreal Injections in Arc Sterile Setting: Safety Profile after More Than 10,000 Treatments by Claudio Furino, Maria Oliva Grassi, Vito Bini, Annalisa Nacucchi, Francesco Boscia, Michele Reibaldi, Nicola Recchimurzo, Giovanni Alessio

“…To report the occurrence of endophthalmitis and other complications after intravitreal injections (IVIs) in the Arc Sterile setting. Methods. A retrospective study that enrolled all patients who underwent IVIs between November 2017 and March 2019, collecting data about the patient’s gender and age, type of injected drug, diagnosis, other ocular pathologies, physician and possible occurrence of endophthalmitis, or other complications. …”
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Integrating a phylogenetic framework for mapping biodiversity patterns to set conservation priorities for an oceanic island flora by Ruth Jaén Molina, Jairo Patiño, Salvador de laCruz, Magui Olangua‐Corral, Águedo Marrero, Carlos García‐Verdugo, Juli Caujapé‐Castells

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Landiolol bolus application for tachycardic dysrhythmia in the prehospital EMS setting – An observational study of a novel concept by Felix Eibensteiner, Mario Krammel, Andrea Kornfehl, Roman Brock, Christoph Veigl, Daniel Grassmann, Thomas Hamp, Hans Domanovits, Patrick Sulzgruber, Sebastian Schnaubelt

“…No allergic reactions, relevant bradycardias or cardiac arrests were detected immediately after Landiolol administration. …”
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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

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Quantitative Analysis of 3-Monochloropropane-1,2-diol in Fried Oil Using Convolutional Neural Networks Optimizing with a Stepwise Hybrid Preprocessing Strategy Based on Fourier Tra... by Xi Wang, Siyi Wang, Shibing Zhang, Jiping Yin, Qi Zhao

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Graph convolution network for fraud detection in bitcoin transactions by Ahmad Asiri, K. Somasundaram

“…We have selected the Elliptic Bitcoin Dataset. This data set is a graph data set generated from an anonymous blockchain. …”
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Outlier Detection and Explanation Method Based on FOLOF Algorithm by Lei Bai, Jiasheng Wang, Yu Zhou

“…Subsequently, the FCM objective function is employed to prune the dataset to extract a candidate set of outliers. Finally, a weighted local outlier factor detection algorithm computes the degree of anomaly for each sample in the candidate set. …”
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Image recoloring detection based on inter-channel correlation by Nuo CHEN, Shuren QI, Yushu ZHANG, Mingfu XUE, Zhongyun HUA

“…Image recoloring is an emerging editing technique that can change the color style of an image by modifying pixel values.With the rapid proliferation of social networks and image editing techniques, recolored images have seriously hampered the authenticity of the communicated information.However, there are few works specifically designed for image recoloring.Existing recoloring detection methods still have much improvement space in conventional recoloring scenarios and are ineffective in dealing with hand-crafted recolored images.For this purpose, a recolored image detection method based on inter-channel correlation was proposed for conventional recoloring and hand-crafted recoloring scenarios.Based on the phenomenon that there were significant disparities between camera imaging and recolored image generation methods, the hypothesis that recoloring operations might destroy the inter-channel correlation of natural images was proposed.The numerical analysis demonstrated that the inter-channel correlation disparities can be used as an important discriminative metric to distinguish between recolored images and natural images.Based on such new prior knowledge, the proposed method obtained the inter-channel correlation feature set of the image.The feature set was extracted from the channel co-occurrence matrix of the first-order differential residuals of the differential image.In addition, three detection scenarios were assumed based on practical situations, including scenarios with matching and mismatching between training-testing data, and scenario with hand-crafted recoloring.Experimental results show that the proposed method can accurately identify recolored images and outperforms existing methods in all three hypothetical scenarios, achieving state-of-the-art detection accuracy.In addition, the proposed method is less dependent on the amount of training data and can achieve fairly accurate prediction results with limited training data.…”
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Web Traffic Anomaly Detection Using Isolation Forest by Wilson Chua, Arsenn Lorette Diamond Pajas, Crizelle Shane Castro, Sean Patrick Panganiban, April Joy Pasuquin, Merwin Jan Purganan, Rica Malupeng, Divine Jessa Pingad, John Paul Orolfo, Haron Hakeen Lua, Lemuel Clark Velasco

“…This led to the addition of derived columns in the training set and manually labeled testing set that was then used to compare the anomaly detection performance of the Isolation Forest model with that of cybersecurity experts. …”
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Study on user behavior profiling in insider threat detection by Yuanbo GUO, Chunhui LIU, Jing KONG, Yifeng WANG

“…Behavior profiling technic using no-labeled historical data to build normal behavior model is an effective way to detect insider attackers. …”
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Network intrusion detection based on improved KNN algorithm by Hongsheng Bao, Jie Gao

“…Therefore, a new three-branch decision soft increment K-nearest neighbor algorithm is proposed, representing the class cluster as an interval set. The interval set’s upper, boundary, and lower bound correspond to the positive, boundary, and negative domains generated by the three-branch decision. …”
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Visual Scheme for the Detection of Mobile Attack on WSN Simulator by Young-Sik Jeong, Hyun-Woo Kim, Jong Hyuk Park

“…This paper also proposes an external detection trace simulator (EDTS) that would make sensing data transmitted between sensors visually provide information on the sensing of external attacks.…”
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Deep learning-enhanced signal detection for communication systems. by Yang Liu, Peng Liu, Yu Shi, Xue Hao

“…Based on this, the study innovatively combines Multiple Input Multiple Output (MIMO) with orthogonal frequency division multiplexing technology to construct a data-driven detection system. The system adopts a Multi-DNN method with a dual-DNN cascade structure and mixed activation function design to optimize the channel estimation and signal detection coordination process of the MIMO part. …”
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FOA-BDNet: A behavior detection algorithm for elevator maintenance personnel based on first-order deep network architecture by Zengming Feng, Tingwen Cao

“…Experiments show that the detection accuracy rate on the self-built data set in this paper is 98.68%, which is 4.41% higher than that of the latest target detection model YOLOv8-s, and the reasoning speed reaches 69.51fps/s, which can be easily deployed in common edge devices and meet the real-time detection requirements for the unsafe behaviors of elevator scene maintenance personnel.…”
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Automated detection of bicycle helmets using deep learning by Felix Wilhelm Siebert, Christoffer Riis, Kira Hyldekær Janstrup, Hanhe Lin, Jakob Kristensen, Oguzhan Gül, Frederik Boe Hüttel

“…In this paper, we develop and test a computer vision-based detection method that can be applied to traffic video data. …”
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Nonnegative Matrix Factorizations Performing Object Detection and Localization by G. Casalino, N. Del Buono, M. Minervini

“…In this paper, we present a prototype system based on some nonnegative factorization algorithms, which differ in the additional properties added to the nonnegative representation of data, in order to investigate if any additional constraint produces better results in general object detection via nonnegative matrix factorizations.…”
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A fear detection method based on palpebral fissure by Rawinan Praditsangthong, Bhattarasiri Slakkham, Pattarasinee Bhattarakosol

“…Three hundred sixty images were derived from horror-thriller-murder movies based on IMDb. This data set was utilized to generate the proposed pattern. …”
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Driver and Path Detection through Time-Series Classification by Mario Luca Bernardi, Marta Cimitile, Fabio Martinelli, Francesco Mercaldo

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