Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program by Adrian H. Zai, Jeremiah G. Ronquillo, Regina Nieves, Henry C. Chueh, Joseph C. Kvedar, Kamal Jethwani

“…The purpose of this study was to validate a previously developed heart failure readmission predictive algorithm based on psychosocial factors, develop a new model based on patient-reported symptoms from a telemonitoring program, and assess the impact of weight fluctuations and other factors on hospital readmission. …”
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Detection of Cyanuric Acid and Melamine in Infant Formula Powders by Mid-FTIR Spectroscopy and Multivariate Analysis by Edwin García-Miguel, Ofelia Gabriela Meza-Márquez, Guillermo Osorio-Revilla, Darío Iker Téllez-Medina, Cristian Jiménez-Martínez, Maribel Cornejo-Mazón, Diana Maylet Hernández-Martínez, Tzayhrí Gallardo-Velazquez

“…Results showed that chemometric models demonstrated a good predictive ability of melamine and cyanuric acid concentrations in infant formulas, showing that this is a rapid and accurate technique to be used in the identification and quantification of these adulterants in infant formulas.…”
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Time-Distributed Vision Transformer Stacked With Transformer for Heart Failure Detection Based on Echocardiography Video by Mgs M. Luthfi Ramadhan, Adyatma W. A. Nugraha Yudha, Muhammad Febrian Rachmadi, Kevin Moses Hanky Jr Tandayu, Lies Dina Liastuti, Wisnu Jatmiko

“…The time-distributed vision transformer learns the spatial feature and then feeds the result to the transformer to learn the temporal feature and make the final prediction afterward. We also proposed a frame sampling algorithm by squeezing the video and sampling the frame after a certain interval. …”
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Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH by Qing-Yu Chen, Shu-Min Yin, Ming-Ming Shao, Feng-Shuang Yi, Huan-Zhong Shi

“…Feature importance and average prediction of age, Adenosine (ADA) and Lactate dehydrogenase (LDH) was analyzed. …”
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Estimation of soil organic carbon content and dynamics in Mediterranean climate regions considering long-term monthly climatic conditions by Lei Shen, Wei Zhang, Duanqiang Zhai, Shuo Han, Shuang Tian

“…Results showed that the introduction of long-term average monthly climate data significantly improved the prediction accuracy of the models. The R2 value of the RF model was enhanced by 0.22, whilst the R2 of the LightGBM model improved by 0.20–0.21. …”
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Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning by Yating Zhan, Min Weng, Yangyang Guo, Dingfeng Lv, Feng Zhao, Zejun Yan, Junhui Jiang, Yanyi Xiao, Lili Yao

“…The signature exhibited a reliable and accurate performance in prognostic prediction across TCGA-train, TCGA-test and GSE32894 cohorts. …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…Considering that the ordinary non-maximum suppression method in dense occlusion scenarios will incorrectly suppress the prediction box of the occluded object, EIOU was used to optimize the non-maximum suppression method. …”
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Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke by Gianluca Brugnara, Michael Baumgartner, Edwin David Scholze, Katerina Deike-Hofmann, Klaus Kades, Jonas Scherer, Stefan Denner, Hagen Meredig, Aditya Rastogi, Mustafa Ahmed Mahmutoglu, Christian Ulfert, Ulf Neuberger, Silvia Schönenberger, Kai Schlamp, Zeynep Bendella, Thomas Pinetz, Carsten Schmeel, Wolfgang Wick, Peter A. Ringleb, Ralf Floca, Markus Möhlenbruch, Alexander Radbruch, Martin Bendszus, Klaus Maier-Hein, Philipp Vollmuth

“…Pseudo-prospective external validation was performed in consecutive patients with suspected AIS from 4 different hospitals during a 6-month timeframe and demonstrated high sensitivity (≥87%) and negative predictive value (≥93%). Benchmarking against two CE- and FDA-approved software solutions showed significantly higher performance for our ANN with improvements of 25–45% for sensitivity and 4–11% for NPV (p ≤ 0.003 each). …”
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Current status and prospects of artificial intelligence in the diagnosis and treatment of bladder tumors by GAN Xiya, WEI Wei

“…Machine learning and deep learning algorithms have played an important role in the imaging detection and diagnosis of bladder tumors, providing high accuracy in tumor detection, grading, and staging predictions. …”
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The Use of Artificial Intelligence in Medical Diagnostics: Opportunities, Prospects and Risks by Nataliia Sheliemina

“…However, the AI use in medicine carries certain risks related to ethics and data privacy, shortcomings in the quality of data for training algorithms, and importance of protecting against cyberthreats. …”
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CLINICAL AND LABORATORY ASPECTS OF DETECTING SPECIFIC IgE ANTIBODIES TO COW’S MILK AND ITS COMPONENTS by N. A. Alkhutova, N. A. Kovyazina, O. L. Zhizhina

“…An immunochemoluminescent assay of specific IgE antibody levels to the cow milk using IMMULITE 2000/XPi analyzer has revealed its good informative value at different approaches to prediction and evaluation of food allergy treatment, both oriented for a critical cutoff value of 3 МU/L, and by monitoring a decrease in antibody levels. …”
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Current Status of Application of Spaceborne GNSS-R Raw Intermediate-Frequency Signal Measurements: Comprehensive Review by Qiulan Wang, Jinwei Bu, Yutong Wang, Donglan Huang, Hui Yang, Xiaoqing Zuo

“…These research results have important application potential in fields such as environmental monitoring, climate change research, and weather prediction, and are expected to provide new technological means for global geophysical parameter retrieval.…”
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Harnessing Artificial Intelligence and Innovative Vaccines for Mpox Diagnosis and Control: A Comprehensive Narrative Review by Excel Onajite Ernest-Okonofua, Zainab Abdullahi Zubairu, Malik Olatunde Oduoye, Maryam Tariq, Syed Muhammad, Zainab Siddiqua, Monica Vuyyuru, Benjamin Wafula, Riaz Akhtar, Abdulbasit Fasasi, Samuel Chinonso Ubechu, Bakare Sikiru Olayinka

“…Reported model accuracies for mpox lesion classification and disease trend prediction ranged from 83 to 99.8%, underscoring the high potential of AI-based tools in this field. …”
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Application of Energy Dispersive X-ray Fluorescence Spectroscopy in Analysis of Heavy Metals in Soil: A Review by Aosong JIANG, Longhua WU, Zhu LI

“…In the future, it is important to continue to explore the causes and magnitude of different matrix effects in various types of soils, and to optimize and improve the quantitative analysis model of ED-XRF spectroscopy; the prediction of the effectiveness of heavy metals in soil through multiple regression analysis is also a field that scholars should focus on.…”
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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Xueyan Ji, Shamsulariffin Bin Samsudin, Muhammad Zarif Bin Hassan, Noor Hamzani Farizan, Yubin Yuan, Wang Chen

“…The proposed method has advantages in long-term prediction (> 500ms), especially at 1000ms, the values of Mean Absolute Error and Mean Per Joint Position Error are 71.1 and 1.04 respectively. …”
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Research progress on shale gas productivity evaluation: concepts, methods and future directions by ZHU Suyang, PENG Zhen, DI Yunting, PENG Xiaolong, LIU Dongchen, GUAN Wenjie

“…These advancements aim to avoid the limitations in existing productivity evolution methods and support the development of robust and rational shale gas productivity evaluation models and methods, providing theoretical guidance for accurate well productivity prediction, production stabilization, and efficient resource development.…”
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UAV Trajectory Control and Power Optimization for Low-Latency C-V2X Communications in a Federated Learning Environment by Xavier Fernando, Abhishek Gupta

“…Moreover, a low-complexity UAV trajectory prediction and vehicle selection method is proposed using federated learning, which exploits related information from past trajectories. …”
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Determinação do coeficiente convectivo de transferência de calor de figos submetidos ao resfriamento rápido Determination of the convective heat transfer coefficient of fig fruits... by Mariangela Amendola, Saul Dussán-Sarria, Anderson A. Rabello

“…The objective was to compare the result with the one determined by fitting an empirical equation from the literature to the experimental data. For the prediction of the temperature, near to the center of fruits, the Fourier law model was considered. …”
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Machine learning-assisted quantitative metabolomics of West African patients with advanced breast cancer by Aboubacar Dit Tietie Bissan, Mathieu Michel, Xavier Dieu, Cinzia Bocca, Awo Emmanuela Hilda Amegonou, Fatoumata Matokoma Sidibe, Madani Ly, Bocary Sidi Koné, Nènè Oumou Kesso Barry, Kletigui Casimir Dembélé, Bakary Cissé, Bourèma Kouriba, Gilles Simard, Delphine Mirebeau-Prunier, Juan Manuel Chao de la Barca, Zahra Ouzzif, Pascal Reynier

“…The data were compared with those of 79 healthy controls using a combination of several machine learning approaches and statistical analyses. The predictive models obtained with the machine learning algorithms were comparable, with the best AUC of 0.878 obtained with ridge logistic regression using Boruta feature selection. …”
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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…The simulation was conducted using a small-batch data scale that best fit the actual production requirements of the steel sheet stock warehouse. The algorithm without the Levy flight speed update strategy exhibited significantly reduced convergence, while the algorithm without the local search strategy showed a marked reduction in diversity. …”
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