Natural language processing for enhanced feedback mechanisms in breast cancer care: a systematic review and comparative exploration by Faezeh Firuzpour, Hamid Reza Saeidnia

“…Through a structured review of 28 relevant studies, we identified key advancements in NLP algorithms for analyzing patient feedback, including their integration with social media, online forums, and Electronic Health Records (EHRs). …”
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Semi-Supervised Learned Autoencoder for Classification of Events in Distributed Fibre Acoustic Sensors by Artem Kozmin, Oleg Kalashev, Alexey Chernenko, Alexey Redyuk

“…Additionally, advanced signal processing algorithms are necessary for accurately determining the location and nature of detected events. …”
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Advancements in Machine Learning (ML): Transforming the Future of Blood Cancer Detection and Outcome Prediction by Wiebke Rösler, Michael Roiss, Corinne Widmer

“…Recent studies demonstrate that ML algorithms can rapidly predict hematologic malignancies and patient outcomes, matching or exceeding the accuracy of experienced hematologists. …”
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Responsible artificial intelligence in Africa: towards policy learning by Paul Plantinga, Kristophina Shilongo, Oarabile Mudongo, Angelique Umubyeyi, Michael Gastrow, Gabriella Razzano

“…In response, we suggest that there is a need for more explicit policy learning, by looking at existing governance capabilities and experiences related to algorithms, automation, data, and digital technology in other countries and in adjacent sectors. …”
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DEEP LEARNING-BASED SUPER-RESOLUTION TECHNIQUES: A COMPARATIVE ANALYSIS WITH RECENT INSIGHTS by Renuka Sambhaji Sindge, Maitreyee Dutta, Jagriti Saini

“…Furthermore, this paper presents future directions for future researchers to follow SR trends with potential DL-based algorithms.…”
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PUBLICATIONS OF HISTORIANS OF THE COSSACK EMIGRATION AS A SOURCE OF INFORMATION ON THE NEW ECONOMIC POLICY IN THE DON AND KUBAN REGIONS (1920-s) by A. Baranov, O. Ratushnyak

“…Conclusions on the closeness of the algorithms of analysis and political focus of the work of historians of the Cossack abroad (P. …”
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Color correction methods for underwater image enhancement: A systematic literature review. by Yong Lin Lai, Tan Fong Ang, Uzair Aslam Bhatti, Chin Soon Ku, Qi Han, Lip Yee Por

“…However, challenges persist across all categories, including algorithmic limitations, data dependency, computational complexity, and performance variability across diverse underwater environments. …”
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Aerosols in the Mixed Layer and Mid-Troposphere from Long-Term Data of the Italian Automated Lidar-Ceilometer Network (ALICENET) and Comparison with the ERA5 and CAMS Models by Annachiara Bellini, Henri Diémoz, Gian Paolo Gobbi, Luca Di Liberto, Alessandro Bracci, Francesca Barnaba

“…Through original ALICENET algorithms, we also derive long-term aerosol vertical layering data, including the mixed aerosol layer (MAL) and elevated aerosol layers (EALs) heights. …”
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Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology by Yinhu Gao, Peizhen Wen, Yuan Liu, Yahuang Sun, Hui Qian, Xin Zhang, Huan Peng, Yanli Gao, Cuiyu Li, Zhangyuan Gu, Huajin Zeng, Zhijun Hong, Weijun Wang, Ronglin Yan, Zunqi Hu, Hongbing Fu

“…The effects and main limitations of AI diagnosis were summarized through comprehensive analysis of research design, algorithmic methods, and experimental results from relevant literature. …”
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Keypoint-based modeling reveals fine-grained body pose tuning in superior temporal sulcus neurons by Rajani Raman, Anna Bognár, Ghazaleh Ghamkhari Nejad, Albert Mukovskiy, Lucas Martini, Martin Giese, Rufin Vogels

“…Leveraging deep learning algorithms that extract body poses from videos of behaving monkeys, applied to a monkey avatar, we investigated neural tuning for pose and viewpoint, targeting fMRI-defined mid and anterior Superior Temporal Sulcus (STS) body patches. …”
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Weed-crop dataset in precision agriculture: Resource for AI-based robotic weed control systemsMendeley Data by Arjun Upadhyay, Sunil G. C, Maria Villamil Mahecha, Joseph Mettler, Kirk Howatt, William Aderholdt, Michael Ostlie, Xin Sun

“…This will enhance the capabilities of DL algorithms to be integrated with robotic weed control platforms for precision weed management.…”
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Targeted Interventional Therapies for the Management of Postamputation Pain: A Comprehensive Review by Dunja Savicevic, Jovana Grupkovic, Uros Dabetic, Dejan Aleksandric, Nikola Bogosavljevic, Uros Novakovic, Ljubica Spasic, Slavisa Zagorac

“…Nevertheless, further research is required to standardize clinical algorithms, optimize therapeutic decision-making and improve long-term outcomes and quality of life for individuals with PAP.…”
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Performance prediction of radio frequency based negative ion source using fusion neural network model by Yu Gu, Chundong Hu, Yang Li, Yuwen Yang, Yahong Xie, Qinglong Cui, Yuanzhe Zhao

“…Notably, the theoretical foundations and associated algorithms of the model are not limited to this ion source. …”
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How low can you go: evaluating electrode reduction methods for EEG-based speech imagery BCIs by Maurice Rekrut, Maurice Rekrut, Johannes Ihl, Tobias Jungbluth, Antonio Krüger, Antonio Krüger

“…In this study, we evaluated several electrode reduction algorithms in combination with various feature extraction and classification methods across three distinct EEG-based speech imagery datasets to identify the optimal number and position of electrodes for SI-BCIs. …”
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MLAS: Machine Learning-Based Approach for Predicting Abiotic Stress-Responsive Genes in Chinese Cabbage by Xiong You, Yiting Shu, Xingcheng Ni, Hengmin Lv, Jian Luo, Jianping Tao, Guanghui Bai, Shusu Feng

“…To construct this model, data from relevant studies regarding responses to these abiotic stresses were compiled, and the protein sequences encoded by abiotic SRGs were converted into numerical representations for subsequent analysis. …”
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Older people and the smart city – Developing inclusive practices to protect and serve a vulnerable population by Aaro Tupasela, Juanita Devis Clavijo, Marjut Salokannel, Christoph Fink

“…Older adults over 60 years of age, public servants and other relevant stakeholders were invited to co-create and test the solution to ensure that their needs and challenges were being addressed by the project. …”
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Proteomic and metabolomic profiles of plasma-derived Extracellular Vesicles differentiate melanoma patients from healthy controls by SM Bollard, J Howard, C Casalou, BS Kelly, K O'Donnell, G Fenn, J O'Reilly, R Milling, M Shields, M Wilson, A Ajaykumar, K Triana, K Wynne, DJ Tobin, PA Kelly, A McCann, SM Potter

“…Proteomic and Metabolomic Analyses were performed, and machine learning algorithms were used to identify potential proteins and metabolites to differentiate the plasma-derived EVs from melanoma patients of different disease stages. …”
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An intelligible AI-driven decision support system for poststroke mobility assessment by Jin Cheng Liaw, Dominik Raab, Malte Weber, Mario Siebler, Harald Hefter, Dörte Zietz, Marcus Jäger, Andrés Kecskeméthy, Francisco Geu Flores

“…Detailed assessment of therapeutic success is relevant to achieving efficacy, but requires expert knowledge, since mobility disorders are complex. …”
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Development and validation of a modified SOFA score for mortality prediction in candidemia patients by Xiaofei Liu, Ranran Ding, Guangming Yang, Yuling Qiao, Zhen Ma, Yaping Feng, Feng Qu, Qiang Meng

“…The mSOFA_3 model demonstrated superior predictive performance across multiple machine learning algorithms, with the logistic regression-based model achieving the highest AUC of 0.826 in the internal validation cohort and 0.813 in the test cohort. …”
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Landslide vulnerability mapping using GIS-based statistical model for sustainable ecosystem management in the Himalayan region of Teesta River basin, India by Subodh Chandra Pal, Tanmoy Biswas, Sumit Ghorai, Chaitanya Baliram Pande, Aznarul Islam, Abu Reza Md. Towfiqul Islam, Edris Alam

“…The landslide inventory data are subdivided into training data sets (70%) for applying algorithms in models and testing data sets (30%) for testing model accuracy. …”
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