Compensation of Speckle Noise in 2D Images from Triangulation Laser Profile Sensors Using Local Column Median Vectors with an Application in a Quality Control System by Paweł Rotter, Dawid Knapik, Maciej Klemiato, Maciej Rosół, Grzegorz Putynkowski

“…Consequently, conventional algorithms for removing fixed pattern noise yield unsatisfactory results when applied to profilometer images. …”
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Potential of diagnostic electron microscopy of calcification, pathological neovascularization and elastolysis in combination with phenotyping of cell populations in large arteries by R. A. Mukhamadiyarov, K. Yu. Klyshnikov, V. A. Koshelev, A. G. Kutikhin

“…Electronic contrast distribution signatures unique for each cell population indicate the possibility of their automated phenotyping using specialized neural network algorithms.…”
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Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…The preprocessing module, composed of Wavelet Transform (WT) and the Maximum Information Coefficient (MIC) algorithms, was used to perform noise reduction and parameter correlation analysis on the raw data, thereby generating enhanced inputs. …”
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EXPERIENCE OF SUCCESSFUL ACNEFORM ERUPTIONS TREATMENT IN PATIENT WITH MULTIPLE MELANOMA by O. V. Minkina, A. S. Dvornikov, P. A. Skripkina, T. A. Gaydina, E. V. Trushina

“…Due to the fact that subsequent traditional anti-acne algorithms of topical and oral treatment was not such effective, there was made a decision to use an alternative supporting external therapy, which did not have similar examples of usage previously. …”
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Trends in the causes of stillbirths over 20 years in Southern Japan by Emi Kino, Yohei Maki, Naoshi Yamada, Yuki Kodama, Shinji Katsuragi, Hiroshi Sameshima, Tsuyomu Ikenoue

“…Investigations to prevent cord-accident stillbirths would be required to further reduce stillbirths in the study region. Establishment of algorithms that allow the identification of the causes of stillbirths would be crucial to reduce instances of stillbirths due to unidentified causes.…”
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Identification of biomarkers related to Escherichia coli infection for the diagnosis of gastrointestinal tumors applying machine learning methods by Tingting Ge, Wei Wang, Dandan Zhang, Xubo Le, Lumei Shi

“…Conclusions: Overall, we identified and validated 8 robust genes related to E. coli applying bioinformatics and machine learning algorithms, providing theoretical foundations for the relationship between E. coli-related dysbiosis and gastrointestinal tumors.…”
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Mammographic Screening as a Tool for Cardiovascular Risk Assessing. Part 2. Association of Breast Arterial Calcification and Cardiovascular Diseases by E. V. Bochkareva, I. V. Kim, E. K. Butina, I. D. Stulin, S. A. Trukhanov, B. A. Rudenko, S. A. Boytsov, O. M. Drapkina

“…It is shown that the addition of BAC to the generally accepted (standard) vascular risk assessment algorithms Framingham Risk Score and Pooled Cohort Equation significantly increases the accuracy of prediction of CHD (p=0.02 and p=0.010, respectively). …”
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Real-time monitoring of maize phenology using ground camera fusion information by Qi Zhao, Yonghua Qu, Dongyi Liu

“…To address these issues, this study combined ground camera and machine learning (ML) algorithms to explore the relationship between spectral and texture information derived from NDVI camera and maize phenology (BBCH), developing a user-friendly real-time maize phenology monitoring stacked ensemble learning (SEL) model. …”
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Comparison Between SAW and TOPSIS Methods in Selection of Broiler Chicken Meat Quality by Pungky Tri Kisworo Adi, Endang Sugiharti, Alamsyah Alamsyah

“…Comparison of these algorithms can facilitate the breeders in choosing a good quality broiler chicken meat.The results of the best farmer recommendation according to comparative method of SAW and TOPSIS. …”
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PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS by Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo

“…This study implements multivariate time series forecasting using gradient boosting algorithms (XGBoost, CatBoost, and LightGBM) to predict cash flow patterns in banking transactions, focusing on constructing reliable prediction intervals. …”
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Application of Machine Learning Models in Optimizing Wastewater Treatment Processes: A Review by Florin-Stefan Zamfir, Madalina Carbureanu, Sanda Florentina Mihalache

“…Thus, this paper identifies gaps in the current research, discusses ML and DL algorithms in the context of optimizing wastewater treatment processes, and identifies future directions for optimizing these processes through data-driven methods. …”
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Assessment of structural changes in the left atrium myocardium according to cardiac magnetic resonance with contrast before and after balloon cryoablation in patients with persiste... by O. V. Stukalova, V. S. Kirilova, O. P. Aparina, E. B. Maykov

“…All patients before and after magnetic resonance imaging underwent cardiac magnetic resonance imaging with delayed contrast using a high-resolution MR pulse sequence (voxel size 1,25x1,25x1,25 mm) before and after cryoablation.The severity of atrial fibrous lesion was calculated automatically using a specialized LGE HEART Analyzer program using algorithms based on the myocardial contrast index with a threshold value of 1.38. …”
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358 Rare disease study identification (RDSI): A natural language processing assisted search and visualization tool for clinical studies of rare diseases by Michael Lin, Jennifer Weis, H M Abdul Fattah, Jungwei Fan

“…Search results contain detailed study information as well as the evidence used by algorithms of the pipeline. Results/Anticipated Results: The RDSI identification results and functions were verified manually and spot-checked by several study investigators. …”
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Severe COVID-19 in Third Trimester Pregnancy: Multidisciplinary Approach by Jerald Pelayo, Gabriella Pugliese, Grace Salacup, Eduardo Quintero, Adeeb Khalifeh, David Jaspan, Bhavna Sharma

“…This report highlights the disease progression of COVID-19 in a pregnant woman, the clinical challenges in the critical care aspect of patient management, and the proposed multidisciplinary strategies utilizing an algorithmic approach to optimize maternal and neonatal outcomes.…”
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Diagnostic accuracy of artificial intelligence models in detecting congenital heart disease in the second-trimester fetus through prenatal cardiac screening: a systematic review an... by Lies Dina Liastuti, Lies Dina Liastuti, Yosilia Nursakina, Yosilia Nursakina

“…Nevertheless, prospective studies with bigger datasets and more inclusive populations are needed to compare AI algorithms to conventional methods.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?…”
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Machine learning for prediction of Helicobacter pylori infection based on basic health examination data in adults: a retrospective study by Qiaoli Wang, Tao Liang, Yuexi Li, Peng Zhou, Xiaoqin Liu

“…Six distinct machine learning algorithms were utilized to construct the predictive models, and their performance was comprehensively evaluated. …”
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Facial Beauty Prediction Combining Dual-Branch Feature Fusion With a Stacked Broad Learning System by Junying Gan, Hantian Chen, Wenchao Xu, Huicong Li, Zhenxin Zhuang, Zhen Chen

“…Facial beauty prediction (FBP) is a key computer vision task that uses algorithms to assess facial attractiveness. Current models rely on single feature extraction, such as using a single convolutional neural network to extract local feature, failing to capture other potentially more important information contained within facial data and limiting feature diversity. …”
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Evaluation of the performance of ERA5, ERA5-Land and MERRA-2 reanalysis to estimate snow depth over a mountainous semi-arid region in Iran by Faezehsadat Majidi, Samaneh Sabetghadam, Maryam Gharaylou, Reza Rezaian

“…Future research could benefit from integrating additional datasets and employing machine learning algorithms to improve snow depth assessments, as these approaches may reduce estimation uncertainties and enhance the understanding of snow dynamics across various regions, ultimately contributing to more reliable hydrological assessments.…”
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Polarimetric SAR Ship Detection Using Context Aggregation Network Enhanced by Local and Edge Component Characteristics by Canbin Hu, Hongyun Chen, Xiaokun Sun, Fei Ma

“…The experimental results show that the proposed method achieves a detection precision of 93.6% and a recall rate of 91.5% on a fully polarized SAR dataset, which are better than other popular network algorithms, verifying the reasonableness and superiority of the method.…”
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Experimental and machine learning based analysis of pervious concrete enhanced with fly ash and silica fume by Siva Shanmukha Anjaneya Babu Padavala, Siva Avudaiappan, Venkatesh Noolu

“…Machine learning (ML) models were also created in order to predict compressive strength based on mix composition and curing age using Orange Data Mining software version 3.36. Five algorithms: KNN, Support Vector Machine (SVM), Artificial Neural Networks (ANN), Decision Tree (DT), and Random Forest (RF), were trained and evaluated. …”
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