DBSCAN and DBCV application to open medical records heterogeneous data for identifying clinically significant clusters of patients with neuroblastoma by Davide Chicco, Luca Oneto, Davide Cangelosi

“…We analyzed these datasets using several clustering techniques and measured the results with the DBCV (Density-Based Clustering Validation) index. Among these algorithms, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) was the only one that produced meaningful results. …”
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Clinically validated graphical approaches identify hepatosplenic multimorbidity in individuals at risk of schistosomiasis by Yin-Cong Zhi, Simon Mpooya, Narcis B. Kabatereine, Betty Nabatte, Christopher K. Opio, Goylette F. Chami

“…Co-occurrence graphs were clinically uninformative with low predictive capacity. Graph learning algorithms with statistical assumptions, e.g. graphical lasso, enabled accurate and clinically valid multimorbidity representations. …”
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Ship Magnetic Signature Classification Using GRU-Based Recurrent Neural Networks by Kajetan Zielonacki, Jaroslaw Tarnawski, Miroslaw Woloszyn

“…Features, advantages and limitations of developed algorithms are derived strictly from the nature of neural networks.…”
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Digital Twin: A Step Towards Smart Cities in Urban Planning, Design and Management by Farshad Shariatpour, Mostafa Behzadfar

“…To achieve this, procedural modelling algorithms have been used in the CityEngine software environment. …”
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ASSESSMENT OF TRANSMISSION EFFECTS BETWEEN “CORRUPTION-DIGITIZATION-ECONOMIC GROWTH” by Adriana Surovičová, Victoria Bozhenko, Anton Boyko, K.Yu. Petrenko

“… The last decade has seen the rapid development of digital information technology, the intellectualization of control systems, the increase in the number and capacity of mobile and computer devices, and the accumulation of large amounts of data and its processing through machine learning algorithms, which inevitably leads to new opportunities for economic development. …”
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Opportunities of Digitalization of Economic Subjects in Educational Process by L. N. Babkina, O. V. Skotarenko

“…Thus, institutions of higher professional education should become so-called points of growth or locomotives of growth of the level of application of information and computer technologies, algorithms for solving economic and management problems based on the use of economic and mathematical methods and models that students master in the process of studying the relevant disciplines. …”
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Predicting Drivers’ Eyes-Off-Road Duration in Different Driving Scenarios by Wei Yuan, Zhuofan Liu, Rui Fu

“…Drivers consecutively direct their gaze to various areas to select relevant information from the traffic environment. …”
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A topic modeling approach for analyzing and categorizing electronic healthcare documents in Afaan Oromo without label information by Etana Fikadu Dinsa, Mrinal Das, Teklu Urgessa Abebe

“…Then it extracts the most relevant document topics and generates weight values for each word in the documents per topic. …”
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Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector by Utsav Pandey, Sanjeet Singh

“…While accounting for the external influences and avoiding the ‘best practice trap’ in the healthcare sector, a set of classification algorithms are used to quantify the impact of external factors on efficiency levels. …”
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Integration of Google Earth Engine, Sentinel-2 images, and machine learning for temporal mapping of total dissolved solids in river systems by Eric Ariel L. Salas, Sakthi S. Kumaran, Robert Bennett, Eric B. Partee, Jason Brownknight, Kellsie Schrack, Bryant Willis

“…This study highlights an advanced approach integrating Google Earth Engine (GEE), remote sensing techniques using Sentinel-2 imagery, and machine learning algorithms to map TDS in a spatially explicit manner. …”
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Modeling the process of searching for operationally significant information from open state information resources by E. Yu. Nikulina, L. A. Obukhova, E. A. Rogozin

“…To solve this problem, it seems possible to use Kohonen neural networks or Hamming algorithms. The apparatus of neural networks will allow you to determine patterns and optimize the search for operationally significant information.…”
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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…The GEO-based feature selection method effectively identified the most relevant predictors, while the Deep-NARMAX model captured temporal dynamics for accurate forecasting. …”
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The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma by Binyu Wang, Di Liu, Danfei Shi, Xinmin Li, Yong Li

“…Gene Set Enrichment Analysis (GSEA) was applied to the most relevant module, designated as the greenyellow module. …”
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Construction of a Prediction Model for Sleep Quality in Embryo Repeated Implantation Failure Patients Undergoing Assisted Reproductive Technology Based on Machine Learning: A Singl... by Zhao Y, Xu C, Qin N, Bai L, Wang X, Wang K

“…Use Lasso regression to screen variables and construct a risk prediction model using six machine learning algorithms. Evaluate the validity of the model using the area under the curve (AUC), and comprehensively evaluate the performance of the model based on F1 score, accuracy, sensitivity, and specificity. …”
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Novel Approaches for the Early Detection of Glaucoma Using Artificial Intelligence by Marco Zeppieri, Lorenzo Gardini, Carola Culiersi, Luigi Fontana, Mutali Musa, Fabiana D’Esposito, Pier Luigi Surico, Caterina Gagliano, Francesco Saverio Sorrentino

“…Articles were chosen and vetted according to their quality, contribution to the field, and relevancy. Results: Convolutional neural networks (CNNs) and other deep learning algorithms are among the AI models included in this paper that have been shown to have excellent sensitivity and specificity in identifying glaucomatous alterations in fundus photos, OCT scans, and visual field tests. …”
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Trade-Offs Between Simplifying Inertial Measurement Unit–Based Movement Recordings and the Attainability of Different Levels of Analyses: Systematic Assessment of Method Variations... by Manu Airaksinen, Okko Räsänen, Sampsa Vanhatalo

“…The IMU data can be used for an algorithmic detection of different postures and movements, which may support more detailed assessments of complex behaviors, such as daily activities. …”
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Differentiating Pulmonary Nodule Malignancy Using Exhaled Volatile Organic Compounds: A Prospective Observational Study by Guangyu Lu, Zhixia Su, Xiaoping Yu, Yuhang He, Taining Sha, Kai Yan, Hong Guo, Yujian Tao, Liting Liao, Yanyan Zhang, Guotao Lu, Weijuan Gong

“…We applied five machine learning (ML) algorithms to develop predictive models which were evaluated using area under the curve (AUC), sensitivity, specificity, and other relevant metrics. …”
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Diagnosis and treatment of synthetic mid-urethral sling complications by Helen E. O’Connell, Christopher K. Harding, Gaurav Khatri, Phyllis Glanc, Eric Bautrant, Sarah Love-Jones, Karen Ward, Henry H. Yao, Ventia Hoe, Charlotte Korte, Nicolle Germano, Sanjeevan Kalavampara, Sherif Mourad, Hashim Hashim

“…The working group includes 2 consumer advocates and relevant medical expertise. The management of complications following SMUS placement is discussed and algorithms are provided for each of the common complications of SMUS. …”
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Efficiently Learning an Encoder That Classifies Token Replacements and Masked Permuted Network-Based BIGRU Attention Classifier for Enhancing Sentiment Classification of Scientific... by Muhammad Inaam Ul Haq, Khalid Mahmood, Qianmu Li, Ashok Kumar Das, Sachin Shetty, Majid Hussain

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A Multi-Modal Attentive Framework That Can Interpret Text (MMAT) by Vijay Kumari, Sarthak Gupta, Yashvardhan Sharma, Lavika Goel

“…Deep learning algorithms have demonstrated exceptional performance on various computer vision and natural language processing tasks. …”
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