Development and Validation of an Interpretable Machine Learning Model for Prediction of the Risk of Clinically Ineffective Reperfusion in Patients Following Thrombectomy for Ischem... by Hu X, Qi D, Li S, Ye S, Chen Y, Cao W, Du M, Zheng T, Li P, Fang Y

“…Four machine learning models were developed: random forest (RF), support vector machine (SVM), decision tree (DT), and k-nearest neighbor (KNN). …”
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Network and systems biology approaches help investigate gene regulatory interactions between Salmonella disease and host in chickens: Model‐based in silico evidence combined with g... by Reza Tohidi, Hoda Javaheri Bargourooshi, Arash Javanmard

“…Methods A two‐step experimental design is followed. To start, we used free computational tools and online bioinformatics resources, including predicting gene function using a multiple association network integration algorithm (geneMania), the Kyoto Encyclopedia of Genes and Genomes, the Annotation, Visualization and Integrated Discovery (DAVID) database and the stimulator of interferon genes. …”
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Validation of salivary uric acid remote self-monitoring for early prediction of hypertensive disorders of pregnancy: study protocol for a prospective, observational, multicentre co... by Isabel Reading, Amarnath Bhide, Ramesh Ganapathy, Baskaran Thilaganathan, Basia Chmielewska

“…We will validate a predictive algorithm that analyses colour data from several consecutive samples to detect patterns that predict whether HDP is likely to occur. …”
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Discovering temporal, spatial, and contextual anomalous social activities from streaming social media datasets by Mete Celik, Ahmet Sakir Dokuz, Alper Ecemis, Emre Erdogmus

“…However, detecting anomalies in streaming social media datasets has many difficulties due to the size, continuous increase, different characteristics (e.g., temporal, spatial, and contextual) of the data, and shortcomings of existing algorithms to handle streaming social media datasets. …”
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Hypotensive episodes on program hemodialysis during dialysis procedure: modern approach for diagnostics, prophylaxis and correction by V. Yu. Shilo, I. Yu. Drachev

“…A new method for prevention and correction of hypotension using ASPC allows to decrease ultrafiltration rate on time preventing a hypotensive episode, decreasing its rates and improving attainment of AP target values (both pre- and post-dialysis) as well as intra-dialysis variation during dialysis procedure.…”
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Navigating Ethical Dilemmas Of Generative AI In Medical Writing by Qurrat Ulain Hamdan, Waleed Umar, Mahnoor Hasan

“…Revolution and innovation are dynamic processes that have and will continue, at an increasing pace due to discoveries and inventions. …”
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Incremental predictive value of liver fat fraction based on spectral detector CT for major adverse cardiovascular events in T2DM patients with suspected coronary artery disease by Min Wang, Tanglin Wei, Li Sun, Yanhua Zhen, Ruobing Bai, Xiaomei Lu, Yue Ma, Yang Hou

“…Detailed clinical data, CCTA imaging features, and LFF determined by SDCT multi-material decomposition algorithm were meticulously recorded. …”
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A Hybrid Automata-Driven Machine Learning Framework for Real-Time Energy Optimization in Smart Buildings by Rikame Rajashri, Ranjan Mritunjay Kr., Jadhav Monali, Wankhede Shrushti, Bankar Sakshi, Bachhav Pranjal

“…Conventional energy forecasting techniques are usually not responsive to dynamic energy environments and, therefore, create inefficiencies in energy distribution. …”
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Effective tweets classification for disaster crisis based on ensemble of classifiers by Christopher Ifeanyi Eke, Kholoud Maswadi, Musa Phiri, Mulenga, Mohammad Imran, Dekera Kwaghtyo, Akeremale Olusola Collins

“…Social media platforms, particularly Twitter, have become an invaluable source for disseminating information during disasters, offering real-time updates on events, crisis reports, and casualty information. …”
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Overview of Startups Developing Artificial Intelligence for the Energy Sector by Naiyer Mohammadi Lanbaran, Darius Naujokaitis, Gediminas Kairaitis, Gabrielė Jenciūtė, Neringa Radziukynienė

“…AI-powered solutions allow for a more accurate prediction of demand, immediate monitoring, and automated decision-making processes, significantly enhancing operational efficiency and sustainability. …”
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Hindcasting Maximum Water Depths in Coastal Watersheds: The Importance of Incorporating Off‐Channel Data and Their Uncertainties in Machine Learning Models by Maryam Pakdehi, Ebrahim Ahmadisharaf

“…Our study provides insights about developing transferable ML models for hindcasting water depths on streams and off‐channel areas in coastal watersheds during extreme events.…”
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Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…The findings deepen our understanding of energy dynamics across various building types and promote a sustainable energy future. …”
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AI-Driven Transcriptome Prediction in Human Pathology: From Molecular Insights to Clinical Applications by Xiaoya Chen, Huinan Xu, Shengjie Yu, Wan Hu, Zhongjin Zhang, Xue Wang, Yue Yuan, Mingyue Wang, Liang Chen, Xiumei Lin, Yinlei Hu, Pengfei Cai

“…Machine learning algorithms and deep learning models excel in extracting meaningful features from diverse biomedical modalities, enabling tools like PathChat and Prov-GigaPath to improve cancer subtyping, therapy response prediction, and biomarker discovery. …”
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FoodSky: A food-oriented large language model that can pass the chef and dietetic examinations by Pengfei Zhou, Weiqing Min, Chaoran Fu, Ying Jin, Mingyu Huang, Xiangyang Li, Shuhuan Mei, Shuqiang Jiang

“…With the increasing complexity of global dietary cultures, there is a growing demand for food intelligence to enable tasks like recipe recommendations and diet-disease correlation discovery. …”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…A key innovation discussed is GluComp, a modular digital health platform designed to improve diabetes management. …”
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Shallow Model and Deep Learning Model for Features Extraction of Images by Saba Qasim Hasan

“…A variety of image preparation techniques or data sets, Different approaches are done to obtain a feature that will be used for artificial intelligence (AI) algorithms that projects involving ML or the trendiest and most well-liked fields, including deep learning. …”
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Automated design framework for excavation retaining structures: Extending IFC standards and integrating BIM with geotechnical simulation by Qiwei Wan, Yuyuan Zhu, Haibin Ding, Wentao Hu, Changjie Xu

“…It integrates the extended IFC standard with mechanical analysis and BIM modeling, significantly advancing structural optimization and rebar detailing. Direct 3D model generation streamlines complex excavation projects, aligning with the trend towards automated, precision-driven design. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…AI also streamlines the pharmaceutical process, from disease diagnosis to the prediction of drug distribution in skin layers, enabling efficient formulation development. …”
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Brachial Plexopathy in Head and Neck Cancer Potentially Related to LET-Dependent RBE by Abanob Hanna, Anthony Casper, Roi Dagan, Hardev S. Grewal, Jiyeon Park, Eric D. Brooks, Erik Traneus, Lars Glimelius, Perry B. Johnson, Mohammad Saki, Yawei Zhang, Twyla R. Willoughby, Julie A. Bradley, Jackson Browne, Mark E. Artz

“…Four years post-treatment, the patient developed progressive right upper extremity paresthesia, weakness, and dysesthesia. …”
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Applications of fault-tolerant control system in the design of wind turbine generation systems: A comprehensive review and future prospects by Arslan Ahmed Amin, Muhammad Irfan, Turki Alsuwian, Saifur Rahman, Ansa Mubarak, Saba Waseem

“…The review also discusses the relevant research gaps and future works, such as using computational algorithms to develop novel material and implementing the utilization of digital twins to improve fault management.…”
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