Urban walkability through different lenses: A comparative study of GPT-4o and human perceptions. by Musab Wedyan, Yu-Chen Yeh, Fatemeh Saeidi-Rizi, Tai-Quan Peng, Chun-Yen Chang

“…Assessing urban environments, particularly walkability, has traditionally relied on computer vision and machine learning algorithms. However, these approaches often fail to capture the subjective and emotional dimensions of walkability, due to their limited ability to integrate human-centered perceptions and contextual understanding. …”
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An Overview of Performance Analysis and Optimization in Coexisting Satellites and Future Terrestrial Networks by Sirine Ben Ati, Hayssam Dahrouj, Mohamed-Slim Alouini

“…., backhaul-access cross-interference, resource coordination, channel modeling, and algorithmic complexity. Finally, we identify several open research issues, e.g., a cognitive radio approach to the considered network, integrated backhaul-access system, integration with emerging disruptive systems, artificial intelligence, and quantum communication technologies for coexisting satellites and future terrestrial networks.…”
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OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis. by Greg Finak, Jacob Frelinger, Wenxin Jiang, Evan W Newell, John Ramey, Mark M Davis, Spyros A Kalams, Stephen C De Rosa, Raphael Gottardo

“…Flow cytometry is used increasingly in clinical research for cancer, immunology and vaccines. Technological advances in cytometry instrumentation are increasing the size and dimensionality of data sets, posing a challenge for traditional data management and analysis. …”
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The Role of Education in Building National Soft Power: An Empirical Analysis From a Global Perspective Using Deep Neural Networks by Yun Bai

“…Finally, we compare the performance of our proposed DNN model with other machine learning algorithms, such as Random Forest and Support Vector Machines, demonstrating superior predictive accuracy. …”
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Using transformers and Bi-LSTM with sentence embeddings for prediction of openness human personality trait by Anam Naz, Hikmat Ullah Khan, Tariq Alsahfi, Mousa Alhajlah, Bader Alshemaimri, Ali Daud

“…The individuals having a sensing nature tends to be more practical and prefer to focus on concrete information whereas the users having intuitive trait type is characterized by a focus on abstract ideas, creative thinking and future-oriented perspectives. In this research work, we aim to explore diverse natural language processing (NLP) based features and apply state of the art deep learning algorithms for openness trait prediction. …”
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The role of epigenetic regulation in pancreatic ductal adenocarcinoma progression and drug response: an integrative genomic and pharmacological prognostic prediction model by Kang Fu, Junzhe Su, Yiming Zhou, Xiaotong Chen, Xiao Hu

“…A machine learning-based prognostic model was constructed using multiple algorithms, including Lasso and Random Survival Forest. …”
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Integrating bioinformatics and machine learning to investigate the mechanisms by which three major respiratory infectious diseases exacerbate heart failure by Yiding Yu, Quancheng Han, Juan Zhang, Jingle Shi, Huajing Yuan, Yitao Xue, Yan Li

“…Our findings enhance the understanding of molecular interactions between respiratory diseases and heart failure, paving the way for future research and therapeutic strategies.…”
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Epidemiological tracking and population assignment of the non-clonal bacterium, Burkholderia pseudomallei. by Julia Dale, Erin P Price, Heidie Hornstra, Joseph D Busch, Mark Mayo, Daniel Godoy, Vanaporn Wuthiekanun, Anthony Baker, Jeffrey T Foster, David M Wagner, Apichai Tuanyok, Jeffrey Warner, Brian G Spratt, Sharon J Peacock, Bart J Currie, Paul Keim, Talima Pearson

“…The approach used here may be valuable for other non-clonal pathogens that lack simple group-defining genetic characteristics and provides a rapid reference for epidemiologists wishing to track the origin of infection without the need to compile population data and learn population assignment algorithms.…”
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Current View on the Postoperative Asthenopic Syndrome Problem in Patients with Corneal Refractive Surgery. Review by I. A. Mushkova, N. V. Maychuk, E. Yu. Markova, L. T. Shamsetdinova

“…In order to correct the disturbed parameters, additional research methods and effective methods of functional treatment of patients in the postoperative period were suggested. …”
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A review on artificial intelligence thermal fluids and the integration of energy conservation with blockchain technology by Abdullah Ayub Khan, Asif Ali Laghari, Syed Azeem Inam, Sajid Ullah, Laila Nadeem

“…In order to support sustainable energy goals, these highlighted machine learning algorithms offer a potent environment for optimising energy flow, temperature regulation, and application stability. …”
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Machine learning-based predictive model for enteral nutrition-associated diarrhea in ICU patients and its nursing applications by Xiaoying Liao, Chunhua Li, Qunyan Liu, Wang Xia, Zhenglin Liu, Jiamao Zhu, Wei Hu, Qionghua Hong

“…LASSO regression was used for feature selection, and 9 machine learning (ML) algorithms were evaluated. Model performance was assessed using metrics such as the area under the receiver operating characteristic curve (AUC). …”
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SFMattingNet: A Trimap-Free Deep Image Matting Approach for Smoke and Fire Scenes by Shihui Ma, Zhaoyang Xu, Hongping Yan

“…Since image matting algorithms compute these alpha values, the quality of the alpha composition directly depends on the performance of the smoke and fire matting methods. …”
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Embedded Anchors Coupled Low-Rank Tensor Learning for Multi-View Intrinsic Subspace Clustering by Yueyao Li, Yanying Mei, Zhenwen Ren, Bin Wu

“…The cubic time complexity of both graph construction and spectral clustering has greatly hindered the application of these algorithms to large-scale scenarios. Several research approaches have dramatically improved the clustering productivity by employing the anchor sampling mechanism. …”
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The Role of Pharmacometrics in Advancing the Therapies for Autoimmune Diseases by Artur Świerczek, Dominika Batko, Elżbieta Wyska

“…Its integration into DDD and translational science, in combination with AI and ML algorithms, holds promise for advancing therapeutic strategies and improving autoimmune patients’ outcomes.…”
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Deep learning radiomics based on MRI for differentiating tongue cancer T - staging by Zhaoyi Lu, Bowen Zhu, Hang Ling, Xi Chen

“…ResNet18 and ResNet50 algorithms were employed to build deep learning models (deep learning radiomics (DLR) resnet18 / DLRresnet50), compared with a radiomics model (Rad) based on 17 optimized features. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…By integrating machine learning (ML) algorithms, such as Gradient Boosting Models and Support Vector Machines, with SHAP-based feature visualization, robust screening methods were applied to ensure the reliability of predictions. …”
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WoE Analysis and Key Risk Factors in Preclinical Development of Medicinal Products: A Review by G. N. Engalycheva, R. D. Syubaev

“…The WoE assessment algorithms and criteria described in this article may be implemented by preclinical study initiators, their research teams, and regulatory experts evaluating medicines.…”
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Incidence, Pathogenesis, Risk Factors, and Treatment of Cystoid Macula Oedema Following Cataract Surgery: A Systematic Review by Lorenzo Ferro Desideri, Kirupakaran Arun, Enrico Bernardi, Nicola Sagurski, Rodrigo Anguita

“…<b>Conclusions:</b> Topical NSAIDs, often combined with periocular steroids, serve as first-line therapy, with periocular steroids offering additional efficacy in resistant cases. Further research is needed to establish optimal treatment algorithms and improve outcomes for patients with post-operative CMO…”
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REALISATION D’UN SYSTEME (PARADIS) POUR LA SYNTHESE DE LA PAROLE ARABE A PARTIR DU TEXTE by Noureddine Chenfour

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NLP for computational insights into nutritional impacts on colorectal cancer care by Shengnan Gong, Xiaohong Jin, Yujie Guo, Jie Yu

“…Colorectal cancer (CRC) is one of the most prominent cancers globally, with its incidence rising among younger adults due to improved screening practices. However, existing algorithms for CRC prediction are frequently trained on datasets that primarily reflect older persons, thus limiting their usefulness in more diverse populations. …”
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