An Attention-Based Residual U-Net for Tumour Segmentation Using Multi-Modal MRI Brain Images by Najme Zehra Naqvi, K. R. Seeja

“…Hence, this research proposes a novel automated deep-learning approach based on U-Net for segmenting Glioma tumours. …”
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Biomechanical Modeling and Evaluation of Buttocks Automatic Assisted Repositioning in Bedridden Patients by Liqing Yang, Ganjun Song, Di Luo, Haotian Xu, Jiamei Han, Mingzhao Xiao, Dingqun Bai, Shan Tian, Wensheng Hou, Jisi Tang, Xin Zhang, Lin Chen

“…Pressure ulcers (PUs) pose a significant challenge in the care of bedridden patients, to which automated tilt nursing beds have emerged as a promising solution. …”
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Implementing Machine Learning for Supply-Demand Shifts and Price Impacts in Farmer Market for Tool and Equipment Sharing by Manik Rakhra, Amitabh Bhargava, Deepshikha Bhargava, Ramandeep Singh, Astha Bhanot, Abdul Wahab Rahmani

“…Several industries have recently seen the replacement of human labor by automated machinery and equipment. Across the globe, farmers’ attitudes on the use of technology in agriculture are divergent. …”
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New proposal for a multimodal imaging approach for the subclinical detection of hydroxychloroquine-induced retinal toxicity in patients with systemic lupus erythematosus by Ricard Cervera, Alfredo Adan, Gerard Espinosa, Jose Rios, Olga Araujo, José Hernández-Rodríguez, Laura Pelegrín, Ricardo P Casaroli-Marano, Halbert Hernández-Negrín, Marc Figueras-Roca, Vanesa Budi, Montse Morató

“…Each patient underwent a comprehensive ophthalmic evaluation, comprising structural tests (spectral-domain optical coherence tomography (SD-OCT), en face OCT, en face OCT angiography (OCTA), fundus autofluorescence (FAF)) and functional tests (automated perimetry for visual field (VF) testing, multifocal electroretinography (mfERG)). …”
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Expert evaluation of large language models for clinical dialogue summarization by David Fraile Navarro, Enrico Coiera, Thomas W. Hambly, Zoe Triplett, Nahyan Asif, Anindya Susanto, Anamika Chowdhury, Amaya Azcoaga Lorenzo, Mark Dras, Shlomo Berkovsky

“…Large language models may provide a successful path for automating clinical dialogue summarization. Privacy concerns and the restricted nature of health records remain challenges for its integration. …”
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Data Augmentation and Machine Learning algorithms for multi-class imbalanced morphometrics data of stingless bees by Daisy Salifu, Lorna Chepkemoi, Eric Ali Ibrahim, Kiatoko Nkoba, Henri E.Z. Tonnang

“…Our results pave the way for the development of smart and automated machine learning applications to complement the existing methods for the identification of stingless bee species.…”
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Information system on microbial collections as a part of bioresource collections portal for Russia’s FASO organizations: a working protocol by F. V. Kazantsev, A. A. Smirnova, A. S. Rozanov, Yu. E. Uvarova, D. A. Afonnikov, S. E. Peltek, S. A. Lashin

“…Registered users – owners of collections – have the opportunity to create and modify records about the storage units of their collections, and to update their description. To automate work with the portal, software access to the database through the REST API has been implemented (http://api.biores.cytogen.ru/ microbes/). …”
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Universal conditional networks (UniCoN) for multi-age embryonic cartilage segmentation with Sparsely annotated data by Nishchal Sapkota, Yejia Zhang, Zihao Zhao, Maria Jose Gomez, Yuhan Hsi, Jordan A. Wilson, Kazuhiko Kawasaki, Greg Holmes, Meng Wu, Ethylin Wang Jabs, Joan T. Richtsmeier, Susan M. Motch Perrine, Danny Z. Chen

“…While DL approaches have been proposed to automate cartilage segmentation, most such models have limited accuracy and generalizability, especially across data from different embryonic age groups. …”
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Cardioattentionnet: advancing ECG beat characterization with a high-accuracy and portable deep learning model by Youfu He, Youfu He, Youfu He, Yu Zhou, Yu Zhou, Yu Qian, Jingjie Liu, Jinyan Zhang, Debin Liu, Qiang Wu, Qiang Wu

“…This situation highlights the necessity for an automated, efficient, and real-time detection method aimed at enhancing diagnostic accuracy and improving patient outcomes.MethodsThe present study is centered on the development of a portable deep learning model for the detection of arrhythmias via electrocardiogram (ECG) signals, referred to as CardioAttentionNet (CANet). …”
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Reflections on COVID-19: A Literature Review of SARS-CoV-2 Testing by Chin Shern Lau, Helen M. L. Oh, Tar Choon Aw

“…They included both nucleocapsid/spike antibodies and automated antigen assays. Early in the pandemic, it was generally agreed that the initial nucleocapsid antibody assays had poor sensitivity when used before 14 days of disease onset, with total or IgG antibodies being preferred over the use of IgM. …”
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<i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables by Lourdes Vega-Hanna, Dídac Casas-Alba, Sol Balsells, Mercè Bolasell, Patricia Rubio, Ana García-García, Oscar García-García, Mar O’Callaghan, Ainhoa Pascual-Alonso, Judith Armstrong, MDS Group, Antonio F. Martinez-Monseny

“…This study aims to (1) develop a specific clinical severity scale, (2) explore its correlation with clinical and molecular variables, and (3) automate diagnosis using the Face2gene platform. <b>Methods</b>: A retrospective study was conducted on genetically confirmed MDS patients who were evaluated at a pediatric hospital between 2012 and 2024. …”
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A novel approach to skin disease segmentation using a visual selective state spatial model with integrated spatial constraints by Yu Bai, Hai Zhou, Hongjie Zhu, Shimin Wen, Binbin Hu, Haotian Li, Huazhang Wang, Daji Ergu, Fangyao Liu

“…Abstract Accurate segmentation of skin lesions is crucial for reliable clinical diagnosis and effective treatment planning. Automated techniques for skin lesion segmentation assist dermatologists in early detection and ongoing monitoring of various skin diseases, ultimately improving patient outcomes and reducing healthcare costs. …”
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A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

“…As a result, the study intends to create an automated tool based on a deep neural network linked with an image-retrieval procedure for recognizing infections in microscopic pictures. …”
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Enhancing university remote language learning through innovative applications of artificial intelligence technologies amidst global challenges by N. Sarnovska, J. Rybinska, Yu. Mykhailichenko

“…By personalizing learning paths, providing intelligent tutoring, incorporating conversational practice, utilizing gamification, automating assessment, and leveraging virtual reality, AI is reshaping language education to be more engaging, effective, and tailored to individual student needs. …”
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Lithological and geochemical characterization of ‘adinole’ artefacts from cave deposits in southwest Wales: A material of choice during the late Middle to Upper Palaeolithic by Richard Bevins, Elizabeth A. Walker, Nick Pearce, Duncan Pirrie, Rob Ixer, Ian Saunders, Matthew Power

“…Standard petrography has been combined with automated SEM-EDS analysis for a single artefact to determine the mineralogy and textures of that artefact, while portable XRF and μXRF have been combined to establish the geochemical characteristics of all twenty-three artefacts analysed. …”
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Healthcare Futures: Opportunities, Challenges and Risks in a Blockchain-Driven Environment by Robert Goldberg, Peter J. Pitts, Jennifer Hinkel

“…By leveraging smart contracts, which automate transactions and ensure trust through pre-defined algorithms, the platform offers a seamless and secure environment for managing complex healthcare data and financial instruments. …”
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Ensemble Learning for Three-dimensional Medical Image Segmentation of Organ at Risk in Brachytherapy Using Double U-Net, Bi-directional ConvLSTM U-Net, and Transformer Network by Soniya Pal, Raj Pal Singh, Anuj Kumar

“…Aim: This article presents a novel approach to automate the segmentation of organ at risk (OAR) for high-dose-rate brachytherapy patients using three deep learning models combined with ensemble learning techniques. …”
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Model of forecasting of material resources and estimated cost at early stages of life cycle of construction objects by M. V. Gureev, A. N. Makarov

“…The training and research were conducted using the automated machine learning (AutoML) method. Based on a comparison of the coefficient of determination R2 and the standard deviation (RMSE), ensembles of models were selected that form a forecast for the volume of material resources and equipment, as well as for the estimated cost with an error range of ±8 %. …”
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Biomarker Profiling for Pyridoxine Dependent Epilepsy in Dried Blood Spots by HILIC-ESI-MS by Elizabeth Mary Mathew, Sudheer Moorkoth, Leslie Lewis, Pragna Rao

“…The newly developed method involves no derivatisation and has a simple sample preparation and a low run time enabling it to be easily automated with a high sample throughput in a cost-effective manner.…”
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SpikeDroidDB: AN INFORMATION SYSTEM FOR ANNOTATION OF MORPHOMETRIC CHARACTERISTICS OF WHEAT SPIKE by M. A. Genaev, E. G. Komyshev, Fu Hao, V. S. Koval, N. P. Goncharov, D. A. Afonnikov

“…The effectiveness of ears’ phenotyping can be improved by the introduction of an automated image processing technology, storage of information in databases, use of machine learning algorithms to analyze this information. …”
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