A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

“…To evaluate the proposed method, eight DL models — Feedforward Neural Network, Recurrent Neural Network, Deep Neural Network, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Bidirectional LSTM, Gated Recurrent Unit (GRU) and Bidirectional GRU were trained on selected features using different FS methods, as well as complete dataset. …”
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Time trends incidence of celiac disease in a Spanish population. by Julia María Cabo Del Riego, María Jesús Núñez-Iglesias, Andrés Blanco Hortas, Tamara Álvarez Fernández, Ignacio Corchero, Silvia Novío, José Paz Carreira, Carmen García-Plata González, José Abel González-Ramirez, Sofia Zaera, Manuel Freire-Garabal Núñez

“…<h4>Background/objective</h4>Very few studies on celiac disease (CD) incidence across all age groups have been carried out so far, particularly in Spain. We evaluate the time trend incidence of CD of children, adults and elderly.…”
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RecompGPT: Generative Pre-Trained Transformers-Assisted Interactive Human Gaze Pattern Learning and Distribution Modeling for Scene Recomposition by Wang Shang, Nassiriah Binti Shaari, Nur Sauri Bin Yahaya, Liu Hao

“…Then, we deploy GPT to learn the distribution of the initial human gaze fixation toward different sceneries. Afterward, these GSPs are refined via a multi-layer aggregation algorithm that encodes deep feature representations into a Gaussian Mixture Model (GMM) to model the distribution of human gaze patterns. …”
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Adaptive Transmission Rate Control for Decentralized Sensing Applications by Stefan Schuhback, Lars Wischhof, Jorg Ott

“…Our algorithm leverages device density information that is locally collected, aggregated, and shared. …”
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Cross-Cultural Sense-Making of Global Health Crises: A Text Mining Study of Public Opinions on Social Media Related to the COVID-19 Pandemic in Developed and Developing Economies by Adham Kahlawi, Firas Masri, Wasim Ahmed, Josep Vidal-Alaball

“…ResultsThe analysis revealed significant regional and temporal differences in collective sense-making during the pandemic. …”
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Effect of Slab Curling on Backcalculated Material Properties of Jointed Concrete Pavements by Tae-Seok Yoo, Jin-Sun Lim, Jin-Hoon Jeong

“…Different backcalculation algorithms produce different elastic moduli which are used as a key indicator of structural capacity of concrete pavements. …”
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Expected Length of the Shortest Path of the Traveling Salesman Problem in 3D Space by Hongtai Yang, Xiaoqian Lu, Xinan Zhou, Rong Zheng, Yugang Liu, Siyu Tao

“…To fill this gap, this research focuses on developing models to estimate the expected length of the shortest path of 3D-TSP. First, different experimental scenarios are designed by combining different service areas and the number of demand points. …”
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A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction by Suleiman Daoud, Ahmad Nasayreh, Khalid M.O. Nahar, Wlla k. Abedalaziz, Salem M. Alayasreh, Hasan Gharaibeh, Ayah Bashkami, Amer Jaradat, Sultan Jarrar, Hammam Al-Hawamdeh, Absalom E. Ezugwu, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Laith Abualigah

“…We first convert the algorithm from continuous to binary, combine it with the K-Nearest Neighbor (KNN) algorithm for classification, and evaluate it on a dataset of brain MRI images collected from King Abdullah Hospital. …”
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Transcriptomic and proteomic analysis reveals wall-associated and glucan-degrading proteins with potential roles in Phytophthora infestans sexual spore development. by Xiaofan Niu, Audrey M V Ah-Fong, Lilianna A Lopez, Howard S Judelson

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Fuzzy Performance between Surface Fitting and Energy Distribution in Turbulence Runner by Zhongwei Liang, Xiaochu Liu, Bangyan Ye, Richard Kars Brauwer

“…Because the application of surface fitting algorithms exerts a considerable fuzzy influence on the mathematical features of kinetic energy distribution, their relation mechanism in different external conditional parameters must be quantitatively analyzed. …”
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Diagnosis of dysphagia in the practice of a family doctor (clinical cases). by О. A. Rosytska, A. V. Chernilovski

“…The article presents diagnostic algorithms for the actions of the ge­neral practitioner-family doctor in the detection of dysphagia and clinical cases of this syndrome of different etiology.…”
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Secondary Intraocular Lens Options in Intraocular Lens Dislocation: A Review by Alexander Maloof, Ava James, Nicholas Pavic, Shane Zhang, Stephanie Wu, Christopher Go

“…A broad review of the literature was performed. We evaluated different techniques for both IOL lens rescue and secondary IOLs, with a focus on the latter. …”
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Study on Tracking Real-Time Target Human Using Deep Learning for High Accuracy by Van-Truong Nguyen, Duc-Tuan Chu

“…Subsequently, the particle filter algorithm is applied to track the target human. The proposed system is evaluated with the different color shirts and complex background conditions. …”
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PECULIARITIES OF ELABORATING AND MAKING COMPLEX MARKETING DECISIONS IN UNSTEADY MANAGEMENT SYSTEMS by S. Karpova, Y. Chupina

“…The paper describes the differences in integrated marketing solutions depending on the stage of instability in the organization. …”
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An effective Key Frame Extraction technique based on Feature Fusion and Fuzzy-C means clustering with Artificial Hummingbird by Sumandeep Kaur, Lakhwinder Kaur, Madan Lal

“…This study proposes a key frame extraction method from a video that (i) first removes insignificant frames by pre-processing, (ii) second, four visual and structural feature differences among the consecutive frames are extracted and aggregated to identify informative frames, (iii) third, to cluster the obtained frames, a hybrid FCM-AHA method is proposed by combining Fuzzy C-means(FCM) with artificial hummingbird optimization algorithm (AHA) to circumvent the local minima trapping problem of FCM, and finally, from each cluster, the two frames having greatest Euclidean distance from all the other frames within a cluster is selected as key frames to remove redundant frames. …”
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Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations by Yuchao Miao, Jiwei Li, Ruigang Ge, Chuanbin Xie, Yaoying Liu, Gaolong Zhang, Mingchang Miao, Shouping Xu

“…We compared the gamma passing rate, dose difference maps, and relevant dose-volume metrics to evaluate the model’s performance. …”
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IVIM-DWI-based radiomic model for preoperative prediction of hepatocellular carcinoma differentiation by ZHUANG Yuxiang, LI Xiaofeng, ZHOU Daiquan

“…Support vector machine (SVM), logistic regression (LR) and random forest (RF) algorithms were utilized to construct different image omics models. …”
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Development of Artificial Intelligent-Based Methodology to Prepare Input for Estimating Vehicle Emissions by Elif Yavuz, Alihan Öztürk, Nedime Gaye Nur Balkanlı, Şeref Naci Engin, S. Levent Kuzu

“…Machine learning has significantly advanced traffic surveillance and management, with YOLO (You Only Look Once) being a prominent Convolutional Neural Network (CNN) algorithm for vehicle detection. This study utilizes YOLO version 7 (YOLOv7) combined with the Kalman-based SORT (Simple Online and Real-time Tracking) algorithm as one of the models used in our experiments for real-time vehicle identification. …”
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Toward value-based care using cost mining: cost aggregation and visualization across the entire colorectal cancer patient pathway by Maura Leusder, Sven Relijveld, Derya Demirtas, Jon Emery, Michelle Tew, Peter Gibbs, Jeremy Millar, Victoria White, Michael Jefford, Fanny Franchini, Maarten IJzerman

“…Per-patient CRC pathway costs ranged from $10,379 AUD to $41,643 AUD, and varied significantly per cancer stage such that e.g. chemotherapy costs in one cancer stage are different to the same chemotherapy regimen in a different stage. …”
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An innovative methodology for segmenting vessel like structures using artificial intelligence and image processing by Reynaldo Villarreal, Sindy Chamorro-Solano, Steffen Cantillo, Roberto Pestana-Nobles, Sair Arquez, Yolanda Vega-Sampayo, Leonardo Pacheco-Londoño, Jheifer Paez, Nataly Galan-Freyle, Cristian Ayala, Paola Amar

“…The enhancement module processes the image using three different varaiables in the same way, which imposes a complexity of O(n) and takes 308,734 ms to execute; the segmentation module evaluates each pixel against its neighbors to correctly segment regions of interes, generating an $$O(n^{2})$$ quadratic complexity and taking 687,509 ms to execute; the masking module makes several runs through the whole image and in several occasions it calls processes of $$O(n\log n)$$ complexity at 581686 microseconds to execute, which makes it not only the most complex but also the most exhaustive part of the program. …”
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