Machine learning and clustering for supporting the identification of active landslides at national scale by Camilla Medici, Alessandro Novellino, Claire Dashwood, Silvia Bianchini

“…Landslide inventory maps (LIMs) are essential for risk management and reduction, but they usually remain an overlooked issue, especially over very large areas, i.e. at a regional or national level. …”
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Sources and trends of black carbon aerosol in the megacity of Nanjing, eastern China, after the China Clean Action Plan and Three-Year Action Plan by A. Abulimiti, A. Abulimiti, Y. Zhang, Y. Zhang, M. Yu, M. Yu, Y. Hong, Y. Hong, Y.-C. Lin, Y.-C. Lin, C. Gul, F. Cao, F. Cao

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Deep Learning–Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach by Sara Abbasi, Khosro Rezaee

“…Method To address this, we developed a novel algorithm for detecting FoG events based on movement signals. …”
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Nutritional Support for Critically Ill Patients (Review) by Igor N. Pasechnik

“…The algorithm of nutritional support is provided based on the phases of critical illness.Conclusion. …”
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Improving pediatric care in Uganda with a digital platform and quality improvement initiative: A retrospective review of Smart Triage + QI. by Rebecca Goertzen, Yashodani Pillay, James Karugaba, Ivan Aine Aye Ishebukara, Ahmad Asdo, Dustin Dunsmuir, Justine Behan, Charly Huxford, Stefanie K Novakowski, Fredson Tusingwire, Ronald Kasyaba, Gloria Kakuru, John Khisa, Stephen Businge, Mike Kyewalyanga, Niranjan Kissoon, J Mark Ansermino

“…<h4>Methods</h4>Smart Triage is a risk prediction algorithm and digital platform that enables healthcare workers to triage patients and track treatments effectively. …”
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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…Multiscale features are then extracted with Inception v3 and combined with principal component analysis (PCA) for dimensionality reduction. Finally, an SVM classification algorithm is employed for personnel detection. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…Such complex motion can impact the ship’s performance and pose a safety risk. This has become an urgent problem in maritime safety. …”
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Cost-Effectiveness Analysis of a Machine Learning–Based eHealth System to Predict and Reduce Emergency Department Visits and Unscheduled Hospitalizations of Older People Living at... by Charlotte Havreng-Théry, Arnaud Fouchard, Fabrice Denis, Jacques-Henri Veyron, Joël Belmin

“…After each home visit, the home care aides completed a questionnaire on participants’ functional status using a smartphone app, and the information was processed in real time by a previously developed machine learning algorithm that identifies patients at risk of an emergency visit within 7 to 14 days. …”
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An Explainable Machine Learning Model for Predicting Macroseismic Intensity for Emergency Management by Federico Mori, Giuseppe Naso

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Acceptability of Guided Symptom Entry and Asynchronous Clinical Communication Software Among Primary Care Staff: Qualitative Study by Riina Raudne, Taavi Tillmann

“…ObjectiveThis study aimed to investigate a patient-facing algorithm-guided symptom-entry software (developed by Certific OÜ, Estonia), which also supports subsequent asynchronous communication, for its acceptability and perceived utility to primary health care providers. …”
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Defining Disease Phenotypes in Primary Care Electronic Health Records by a Machine Learning Approach: A Case Study in Identifying Rheumatoid Arthritis. by Shang-Ming Zhou, Fabiola Fernandez-Gutierrez, Jonathan Kennedy, Roxanne Cooksey, Mark Atkinson, Spiros Denaxas, Stefan Siebert, William G Dixon, Terence W O'Neill, Ernest Choy, Cathie Sudlow, UK Biobank Follow-up and Outcomes Group, Sinead Brophy

“…<h4>Objectives</h4>1) To use data-driven method to examine clinical codes (risk factors) of a medical condition in primary care electronic health records (EHRs) that can accurately predict a diagnosis of the condition in secondary care EHRs. 2) To develop and validate a disease phenotyping algorithm for rheumatoid arthritis using primary care EHRs.…”
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Dynamic Bayesian network modeling for longitudinal data on child undernutrition in Ethiopia (2002–2016) by Getnet Bogale Begashaw, Getnet Bogale Begashaw, Temesgen Zewotir, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Haile Mekonnen Fenta

“…We used a built-in Bayes server tool to identify potential features, followed by building the structure of the directed acyclic graph using a structural learning algorithm. The maximum posterior is determined using the relevance tree algorithm. …”
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Addressing imbalanced data classification with Cluster-Based Reduced Noise SMOTE. by Javad Hemmatian, Rassoul Hajizadeh, Fakhroddin Nazari

“…CRN-SMOTE combines SMOTE for oversampling minority classes with a novel cluster-based noise reduction technique. In this cluster-based noise reduction approach, it is crucial that samples from each category form one or two clusters, a feature that conventional noise reduction methods do not achieve. …”
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Neutrosophic OWA-TOPSIS Model for Decision-Making in AI Systems with Large Volumes of Data by Juan Roberto Pereira Salcedo, Karla Melissa Ruiz Quezada, Edison Luis Cruz Navarrete, Pedro Manuel García Arias

“…This is problematic when engaging multi-criteria decision making with big datadriven projects like infiltration of personalized suggestions, AI-based medical diagnostics, and risk reduction efforts where any decision making with deficient data can reduce effective capabilities. …”
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Machine Learning for Earthquake Emergency Evacuation: Site Selection and Neighborhood Navigation by Amirmasoud Amiran, Behrouz Behnam, Sanaz Seyedin

“…By employing an artificial neural network model informed by data from San Francisco&#x2014;a city with similar seismic risks, urban structure, building types, and population density&#x2014;this study achieved a 23% reduction in the average minimum distance from each parcel to the nearest emergency evacuation center compared to the current conditions. …”
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Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article by Jonti Evan Shepherd, Elad Sagi, Gal Zagron, Eyal Ben-Dor

“…This integrative workflow combining rigorous field calibration, multi-algorithm spectral filtering, and exhaustive validation, demonstrates that orbit-based hyperspectral data can reliably map asbestos hazards at scale, guiding timely emergency response and long-term remediation in high-risk settings.…”
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Clinical and Epidemiological Characteristics of Infections Associated with Surgery and Treatment of Oncological Diseases by G. G. Badamshina, V. B. Ziatdinov, L. M. Fatkhutdinova, G. M. Тrukhina, B. A. Bakirov, A. V. Tutelian, G. Sh. Isaeva

“…Microbiological monitoring of emerging HAIs is an efficient tool for managerial decision making and the development of an algorithm for anti-epidemic measures in the departments and the hospital as a whole for the reduction of risk of infection.…”
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Teleoperation system for multiple robots with intuitive hand recognition interface by Lucas Alexandre Zick, Dieisson Martinelli, André Schneider de Oliveira, Vivian Cremer Kalempa

“…Abstract Robotic teleoperation is essential for hazardous environments where human safety is at risk. However, efficient and intuitive human–machine interaction for multi-robot systems remains challenging. …”
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The use of ridge regression for estimating the severity of acute pancreatitis by D. V. Cherdantsev, A. V. Stroev, E. S. Mangalova, N. V. Kononova, O. V. Chubarova

“…The quantile transformation allows features to be brought to a uniform distribution in order to reduce the risk of excluding significant features. Ridge regression was used in combination with an algorithm for sequential reduction of attribute space.Results. …”
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Investigation and optimization of battery thermal management system based on composite phase change material and variable wall liquid cooling plate by Xiaoyong Gu, Wenbo Lei, Jiacheng Xi, Mengqiang Song

“…To mitigate the risk of thermal runaway in lithium-ion batteries, an efficient battery thermal management system (BTMS) assumes paramount importance. …”
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