Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…Propensity score matching (PSM) and machine learning algorithms were used for confounder adjustment and feature selection.ResultsAfter PSM, 1,429 patients with ARF were included (374 metformin users; 1,055 non-users). …”
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The Emergence of AI-Driven Virtual Hospitals: Redefining Patient Care Beyond Physical Boundaries by Ifrah Hameed, Hafiz Muhammad Haseeb Khaliq

“…The involvement of AI in the development of virtual hospitals has transformed diagnostics and clinical decision-making. Sophisticated AI algorithms have started to analyze complex types of medical data such as medical images, patient reports, and histories. …”
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Opportunistic Diagnostics of Dental Implants in Routine Clinical Photon-Counting CT Acquisitions by Maurice Ruetters, Holger Gehrig, Christian Mertens, Sinan Sen, Ti-Sun Kim, Heinz-Peter Schlemmer, Christian H. Ziener, Stefan Schoenberg, Matthias Froelich, Marc Kachelrieß, Stefan Sawall

“…This study evaluates the diagnostic utility of PCCT for visualizing peri-implant structures in routine clinical photon-counting CT acquisitions and assesses the influence of metal artifact reduction (MAR) algorithms on image quality. Ten dental implants were retrospectively included in this IRB-approved study. …”
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The multiple uses of artificial intelligence in exercise programs: a narrative review by Alberto Canzone, Alberto Canzone, Giacomo Belmonte, Antonino Patti, Domenico Savio Salvatore Vicari, Domenico Savio Salvatore Vicari, Fabio Rapisarda, Valerio Giustino, Patrik Drid, Antonino Bianco

“…BackgroundArtificial intelligence is based on algorithms that enable machines to perform tasks and activities that generally require human intelligence, and its use offers innovative solutions in various fields. …”
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FPGA-Accelerated Sparse Subset Segmentation Using ADMM for High-Resolution Imagery by Rupali Karthikeyan, Deep Amit Lodaya, Rama Muni Reddy Yanamala, Rayappa David Amar Raj, K. Krishna Prakasha, T. Subeesh, V. Anandkumar, Archana Pallakonda

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Aβ status assessment in a hypothetical scenario prior to treatment with disease‐modifying therapies: Evidence from 10‐year real‐world experience at university memory clinics by Matthias Brendel, Tandis Parvizi, Johannes Gnörich, Christof Elias Topfstedt, Katharina Buerger, Daniel Janowitz, Boris‐Stephan Rauchmann, Robert Perneczky, Carolin Kurz, Dirk Mehrens, Wolfgang G. Kunz, Julia Kusche‐Palenga, Agnes Bernadette Kling, Antonia Buchal, Elizabet Nestorova, Sara Silvaieh, Raphael Wurm, Tatjana Traub‐Weidinger, Sigrid Klotz, Günther Regelsberger, Axel Rominger, Alexander Drzezga, Johannes Levin, Elisabeth Stögmann, Nicolai Franzmeier, Günter U. Höglinger

“…We evaluated Aβ levels in cerebrospinal fluid (Aβ CSF) and Aβ levels in positron emission tomography (Aβ PET) biomarkers in a real‐world memory‐clinic setting to develop an efficient algorithm for clinical use. METHODS Patients were evaluated for AD‐related Aβ pathology from two independent cohorts (Ludwig Maximilian University [LMU], n = 402, and Medical University of Vienna [MUV], n = 144). …”
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Modeling and validation of wearable sensor-based gait parameters in Parkinson’s disease patients with cognitive impairment by Guo Hong, Guo Hong, Fengju Mao, Fengju Mao, Mingming Zhang, Fei Zhang, Fei Zhang, Xiangcheng Wang, Kang Ren, Kang Ren, Zhonglue Chen, Zhonglue Chen, Xiaoguang Luo, Xiaoguang Luo

“…The logistic regression model demonstrated superior predictive performance (test set AUC: 0.957), outperforming other machine learning algorithms. …”
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Multiplex immunophenotyping of human acute myeloid leukemia patients revealed single -cell heterogeneity with special attention on therapy sensitive and therapy resistant subpopula... by Nikolett Gémes, Benedek Rónaszéki, Szabolcs Modok, Zita Borbényi, Imre Földesi, Éva Trucza, Blanka Godza, Zsuzsanna László, Balázs Csernus, László Krenács, Enikő Bagdi, Enikő Szabó, László G. Puskás, László G. Puskás, Valeria Bertagnolo, Gábor J. Szebeni, Gábor J. Szebeni, Gábor J. Szebeni

“…Unsupervised clustering algorithms such as Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) and Flow cytometry data that builds Self-Organizing Maps (FlowSOM) were used to reveal the LAIP. …”
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Individual patient variability with the application of the kidney failure risk equation in advanced chronic kidney disease. by Christopher McCudden, Ayub Akbari, Christine A White, Mohan Biyani, Swapnil Hiremath, Pierre Antoine Brown, Navdeep Tangri, Scott Brimble, Greg Knoll, Peter G Blake, Manish M Sood

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Rapid and accurate multi-phenotype imputation for millions of individuals by Lin-Lin Gu, Hong-Shan Wu, Tian-Yi Liu, Yong-Jie Zhang, Jing-Cheng He, Xiao-Lei Liu, Zhi-Yong Wang, Guo-Bo Chen, Dan Jiang, Ming Fang

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miR-146a deficiency in hematopoietic cells is not involved in the development of atherosclerosis. by Alberto Del Monte, Ana B Arroyo, María J Andrés-Manzano, Nuria García-Barberá, María S Caleprico, Vicente Vicente, Vanessa Roldán, Rocío González-Conejero, Constantino Martínez, Vicente Andrés

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Crosstalk between the serine/threonine kinase StkP and the response regulator ComE controls the stress response and intracellular survival of Streptococcus pneumoniae. by Germán E Piñas, Nicolás M Reinoso-Vizcaino, Nubia Y Yandar Barahona, Paulo R Cortes, Rosario Duran, Chandan Badapanda, Ankita Rathore, Dario R Bichara, Melina B Cian, Nadia B Olivero, Daniel R Perez, José Echenique

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CHILES. IX. Observational and Simulated H i Content and Star Formation of Blue Galaxies in Different Cosmic Web Environments by Nicholas M. Luber, Farhanul Hasan, J. H. van Gorkom, D. J. Pisano, Joseph N. Burchett, Julia Blue Bird, Hansung B. Gim, Kelley M. Hess, Lucas R. Hunt, David C. Koo, Sushma Kurapati, Danielle Lucero, Nir Mandelker, Martin Meyer, Emmanuel Momjian, Daisuke Nagai, Joel R. Primack, Min S. Yun

“…CHILES observes a decline in the H i fraction from filament cores to voids, exactly the opposite of the trend predicted by TNG. CHILES observes an increase in H i fraction at z  = 0.5 → 0 in the voids, while TNG predicts an increase in this time in all environments. …”
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A Spatiotemporal Feature Extraction Technique Using Superlet-CNN Fusion for Improved Motor Imagery Classification by Neha Sharma, Manoj Sharma, Amit Singhal, Nuzhat Fatema, Vinay Kumar Jadoun, Hasmat Malik, Asyraf Afthanorhan

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An Empirically Validated Framework for Automated and Personalized Residential Energy-Management Integrating Large Language Models and the Internet of Energy by Vinícius Pereira Gonçalves, Andre Luiz Marques Serrano, Gabriel Arquelau Pimenta Rodrigues, Matheus Noschang de Oliveira, Rodolfo Ipolito Meneguette, Guilherme Dantas Bispo, Maria Gabriela Mendonça Peixoto, Geraldo Pereira Rocha Filho

“…The system combines real-time monitoring, machine learning algorithms for behavioral analysis, and natural language processing to deliver personalized, actionable recommendations through a conversational interface. …”
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“Dictionary of immune responses” reveals the critical role of monocytes and the core target IRF7 in intervertebral disc degeneration by Peichuan Xu, Peichuan Xu, Kaihui Li, Jinghong Yuan, Jinghong Yuan, Jiangminghao Zhao, Jiangminghao Zhao, Huajun Pan, Huajun Pan, Chongzhi Pan, Chongzhi Pan, Wei Xiong, Wei Xiong, Jianye Tan, Jianye Tan, Tao Li, Tao Li, Guanfeng Huang, Guanfeng Huang, Xiaolong Chen, Xiaolong Chen, Xinxin Miao, Dingwen He, Xigao Cheng, Xigao Cheng

“…Furthermore, ten algorithms identified three hub genes. Both experiments conducted in vitro and in vivo have conclusively shown that IRF7 serves as a crucial target for the treatment of IDD, and its knockdown alleviates IDD. …”
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Integrating machine learning models with multi-omics analysis to decipher the prognostic significance of mitotic catastrophe heterogeneity in bladder cancer by Haojie Dai, Zijie Yu, You Zhao, Ke Jiang, Zhenyu Hang, Xin Huang, Hongxiang Ma, Li Wang, Zihao Li, Ming Wu, Jun Fan, Weiping Luo, Chao Qin, Weiwen Zhou, Jun Nie

“…Conclusion The model we developed was a powerful predictive tool for BLCA prognosis and revealed the impact of mitotic catastrophe heterogeneity on BLCA in multiple dimensions, which then guided clinical decision-making. …”
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Machine learning and multi-omics analysis reveal key regulators of proneural–mesenchymal transition in glioblastoma by Can Xu, Jin Yang, Huan Xiong, Xiaoteng Cui, Yuhao Zhang, Mingjun Gao, Lei He, Qiuyue Fang, Changxi Han, Wei Liu, Yangyang Wang, Jin Zhang, Ying Yuan, Zhaomu Zeng, Ruxiang Xu

“…The TIDE algorithm was used to examine immunotherapy scores. …”
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Diagnosis and detection of bone fracture in radiographic images using deep learning approaches by Theyazn Aldhyani, Zeyad A. T. Ahmed, Bayan M. Alsharbi, Sultan Ahmad, Sultan Ahmad, Mosleh Hmoud Al-Adhaileh, Ahmed Hassan Kamal, Mohammed Almaiah, Jabeen Nazeer

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Artificial intelligence (AI) in restorative dentistry: current trends and future prospects by Mariya Najeeb, Shahid Islam

“…Key challenges include data privacy concerns, algorithmic bias, interpretability of AI decision-making processes, and the need for standardized AI training programs in dental education. …”
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