OCTNet: A Modified Multi-Scale Attention Feature Fusion Network with InceptionV3 for Retinal OCT Image Classification by Irshad Khalil, Asif Mehmood, Hyunchul Kim, Jungsuk Kim

“…In recent years, Deep Learning (DL) and Machine Learning (ML) algorithms have become essential tools, particularly in medical image classification, and are widely used to classify and identify various diseases. …”
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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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Automated Calibration of SWMM for Improved Stormwater Model Development and Application by Hossein Ahmadi, Durelle Scott, David J. Sample, Mina Shahed Behrouz

“…The tool also supports parallelized optimization algorithms and utilizes Application Programming Interfaces (APIs) to dynamically update SWMM model parameters, accelerating both model execution and convergence. …”
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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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Liquid metal phase change materials for thermal management of electronics by Yuchen Yao, Wei Li, Jing Liu, Zhongshan Deng

“…In addition, the mathematical models and related numerical algorithms for interpreting the phase change heat transfer mechanisms of LM are illustrated. …”
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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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Identification of gene signatures associated with lactation for predicting prognosis and treatment response in breast cancer patients through machine learning by Jinfeng Zhao, Longpeng Li, Yaxin Wang, Jiayu Huo, Jirui Wang, Huiwen Xue, Yue Cai

“…Lactylation-related gene signature (LRS) was constructed by 15 machine learning algorithms, and the relationship between LRS and tumor microenvironment (TME) as well as drug sensitivity was analyzed. …”
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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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Revolutionize 3D-Chip Design With Open3DFlow, an Open-Source AI-Enhanced Solution by Yifei Zhu, Zhenxuan Luan, Dawei Feng, Weiwei Chen, Lei Ren, Zhangxi Tan

“…<italic>Open3DFlow</italic>&#x2019;s open-source nature allows seamless integration of custom AI optimization algorithms. As a showcase, we leverage large language models (LLMs) to help the bonding pad placement. …”
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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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Mf-net: multi-feature fusion network based on two-stream extraction and multi-scale enhancement for face forgery detection by Hanxian Duan, Qian Jiang, Xin Jin, Michal Wozniak, Yi Zhao, Liwen Wu, Shaowen Yao, Wei Zhou

“…Current face forgery detection algorithms achieve high detection accuracy within-dataset. …”
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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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