Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…Materials for patients included a toolkit (in written and video vignette form). Patients were also invited to a biweekly anonymous chat group. …”
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Machine learning–guided single-cell multiomics uncovers GDF15-driven immunosuppressive niches in NSCLC: A translational framework for overcoming anti-PD-1 resistance by Xianfei Zhang, Zhengxin Yin, Xueyu Chen, Nengchong Zhang, Shengjia Yu, Congcong Zhu, Lianggang Zhu, Liulan Shao, Bin Li, Runsen Jin, Hecheng Li

“…CD8+ T cell infiltration was also substantially enhanced (81.62±4.79 % [SH1] and 123.50±10.02 % [SH2] vs. 29.63±22.17 % [EV], p<0.05). …”
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Remote sensing-based maize growth process parameters revel the maize yield: a comparison of field- and regional-scale by Minghan Cheng, Xiuliang Jin, Chenwei Nie, Kaihua Liu, Tianao Wu, Yuping Lv, Shuaibing Liu, Xun Yu, Yi Bai, Yadong Liu, Lin Meng, Xiao Jia, Yuan Liu, Lili Zhou, Fei Nan

“…This method not only facilitates the optimization of agronomic practices based on UAV observations but also supports the decision of regional agricultural policies based on satellite observations. …”
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The most common errors in automatic ECG interpretation by Krzysztof Kraik, Krzysztof Kraik, Irena Anna Dykiert, Irena Anna Dykiert, Joanna Niewiadomska, Joanna Niewiadomska, Marta Ziemer-Szymańska, Karolina Mikołajczak, Karolina Mikołajczak, Mikołaj Kreń, Mikołaj Kreń, Piotr Kukiełka, Piotr Kukiełka, Adrian Martuszewski, Adrian Martuszewski, Tomasz Harych, Rafał Poręba, Paweł Gać, Małgorzata Poręba

“…It is a non-invasive, widely available and relatively cheap method used mainly in the diagnostics of arrhythmias and a variety of other pathologies, including conduction disturbances and ischemia. ECG is also used to evaluate the activity of a pacemaker or other implantable devices. …”
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The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in context by Xiao-Bin Huang, Tian Tang, Jin-Jin Chen, Yuan-Yuan Zhang, Chen-Long Lv, Qiang Xu, Guo-Lin Wang, Ying Zhu, Yue-Hong Wei, Simon I. Hay, Li-Qun Fang, Wei Liu

“…Aanaplasma phagocytophilum was also detected in the widest range of wildlife (208 species), followed by Ehrlichia chaffeensis (46 species), Candidatus Neoehrlichia mikurensis (36 species), Ehrlichia canis (35 species), and A. bovis (32 species). …”
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Disease activity and treatment response in early rheumatoid arthritis: an exploratory metabolomic profiling in the NORD-STAR cohort by Tahzeeb Fatima, Yuan Zhang, Georgios K. Vasileiadis, Araz Rawshani, Ronald van Vollenhoven, Jon Lampa, Bjorn Gudbjornsson, Espen A. Haavardsholm, Dan Nordström, Gerdur Gröndal, Kim Hørslev-Petersen, Kristina Lend, Marte S. Heiberg, Merete Lund Hetland, Michael Nurmohamed, Mikkel Østergaard, Till Uhlig, Tuulikki Sokka-Isler, Anna Rudin, Cristina Maglio

“…We also found 17 baseline metabolites associated with remission at 24 weeks in the overall cohort, including malic acid (β=-0.4), cytidine (β = 0.4), arginine (β = 0.3), and citrulline (β = 0.2), as well as specific metabolites and metabolic pathways associated with remission in the four treatment arms. …”
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Breast tumors from ATM pathogenic variant carriers display a specific genome-wide DNA methylation profile by Nicolas M. Viart, Anne-Laure Renault, Séverine Eon-Marchais, Yue Jiao, Laetitia Fuhrmann, Sophia Murat El Houdigui, Dorothée Le Gal, Eve Cavaciuti, Marie-Gabrielle Dondon, Juana Beauvallet, Virginie Raynal, Dominique Stoppa-Lyonnet, Anne Vincent-Salomon, Nadine Andrieu, Melissa C. Southey, Fabienne Lesueur

“…Specifically, the methylation pattern of 27 key gene promoters was predictive of ATM PV status of the women. These genes may also represent new medical prevention and therapeutic targets for these women.…”
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Exploring fecal microbiota signatures associated with immune response and antibiotic impact in NSCLC: insights from metagenomic and machine learning approaches by Wenjie Han, Wenjie Han, Yuhang Zhou, Yuhang Zhou, Yiwen Wang, Yiwen Wang, Xiaolin Liu, Tao Sun, Tao Sun, Junnan Xu, Junnan Xu, Junnan Xu

“…The findings not only underscore the prognostic relevance of specific taxa but also establish a foundation for developing microbiome-informed, personalized immunotherapeutic strategies.…”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…By combining field measurements, questionnaire surveys, and advanced machine learning algorithms, the research explores the impact of green space characteristics on emotional restoration, cognitive enhancement, and stress relief. …”
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Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning by Bin He, Yan Cheng, Juan Wang, Ya Zhan, YanQun Liu

“…In the electrical remodeling investigation, ion channel gene sets and gene expression data were utilized alongside LASSO and SVM machine-learning algorithms combined with ROC curve analysis. This approach ultimately identified ANO1 and GRIK2 as the characteristic ion channel genes for AF. …”
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Integrative review of artificial intelligence applications in nursing: education, clinical practice, workload management, and professional perceptions by Rabie Adel El Arab, Omayma Abdulaziz Al Moosa, Mette Sagbakken, Ahmed Ghannam, Fuad H. Abuadas, Joel Somerville, Joel Somerville, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair

“…Study quality was assessed using the Mixed Methods Appraisal Tool (MMAT), and the risk of bias evaluated through ROBINS-I.ResultsThis review encompassed 25 studies, from which six overarching themes emerged.Education and trainingAI-powered simulations and content-creation platforms enriched nursing curricula by presenting realistic clinical scenarios, which consistently yielded deeper student engagement, enhanced case-management performance, and higher satisfaction scores. Learners also reported an increased cognitive load and heightened stress levels when navigating these more complex, AI-driven activities.Clinical decision support and monitoringAI-enabled alert algorithms and wearable sensors enabled nurses to detect subtle signs of patient deterioration and fever significantly earlier than conventional methods, supporting timelier clinical interventions. …”
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Identification of stable reference genes and differential miRNA expression in Sri Lankan type 2 diabetes mellitus patients: a cross-sectional study by Palihaderu Arachchige Dineth Supasan Palihaderu, Balapuwaduge Isuru Layan Madusanka Mendis, Jayasekara Mudiyanselage Krishanthi Jayarukshi Kumari Premarathne, Wajjakkara Kankanamlage Ruwin Dias, Swee Keong Yeap, Wan Yong Ho, Arosha Sampath Dissanayake, Iyanthimala Harshini Rajapakse, Panduka Karunanayake, Upul Senarath, Dilan Amila Satharasinghe

“…Sri Lankan type 2 diabetic patients also had increased hsa-miR-29a-3p and hsa-miR-375-3p levels. …”
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Spatial patterns and MRI-based radiomic prediction of high peritumoral tertiary lymphoid structure density in hepatocellular carcinoma: a multicenter study by Juan Chen, Xiong Chen, Kai Fu, Lan Zhou, Shichao Long, Mengsi Li, Linhui Zhong, Aerzuguli Abudulimu, Wenguang Liu, Deng Pan, Ganmian Dai, Yigang Pei, Wenzheng Li

“…Radiomic features were extracted from intratumoral and peritumoral regions of interest and analyzed using machine learning algorithms to develop a predictive classifier. The classifier’s performance was evaluated using the area under the curve (AUC), with prognostic and predictive value assessed across four independent cohorts and in a dual-center outcome cohort of 41 patients who received immunotherapy.Results Patients with HCC and a high pTLS density experienced prolonged median overall survival (p&lt;0.05) and favorable immunotherapy response (p=0.03). …”
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Research on wave measurement and simulation experiments of binocular stereo vision based on intelligent feature matching by Junjie Wu, Junjie Wu, Shizhe Chen, Shizhe Chen, Shizhe Chen, Shixuan Liu, Shixuan Liu, Shixuan Liu, Miaomiao Song, Miaomiao Song, Miaomiao Song, Bo Wang, Bo Wang, Bo Wang, Qingyang Zhang, Qingyang Zhang, Yushang Wu, Yushang Wu, Yushang Wu, Zhuo Lei, Zhuo Lei, Zhuo Lei, Jiming Zhang, Jiming Zhang, Jiming Zhang, Xingkui Yan, Xingkui Yan, Xingkui Yan, Bin Miao, Bin Miao, Bin Miao

“…To improve the discontinuity and low accuracy in disparity maps from traditional wave image matching algorithms, this paper proposes the use of a high-precision stereo matching method based on Pyramid Stereo Matching Network (PSM-Net).A 3D reconstruction method integrating Scale-Invariant Feature Transform (SIFT) with stereo matching was also introduced to overcome the limitations of template matching and interleaved spectrum methods, which only provide 2D data and fail to capture the full 3D motion of waves. …”
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Evaluation of Knowledge Management Maturity Level in Iranian Audiovisual Archives Based on the APQC Model by Sepideh Ciruskabiri, Atefeh Sharif, Saeed Rezaei Sharifabadi, Mohammad Hassanzadeh

“…Moreover, investment in modernizing technological infrastructures and integrating innovative tools—such as artificial intelligence and machine learning algorithms—can markedly enhance the processes of data collection, storage, and retrieval. …”
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Progress and key technology analysis of bronchoscopic robot by Xingguang DUAN, Dongsheng XIE, Fengxinyun FANG, Rui HE, Changsheng LI

“…A detailed understanding of these technical components not only provides insights into how the technology operates but also identifies potential areas for future refinement. …”
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Antibiogram use on dairy cattle for bovine respiratory disease: Factors associated with bacterial pathogen identification and prediction of bacterial recovery using machine learnin... by Hugo F. Monteiro, Alejandro Hoyos-Jaramillo, Adriana Garzon, Heather M. Fritz, Craig C. Miramontes, Isabelle M. Matos, Terry W. Lehenbauer, Sharif Aly, Fabio S. Lima, Richard V. Pereira

“…For factors associated with the culture-positive of M. haemolytica in BRD clinical cases, an interaction was also observed between age and season, but the farm further played a role in the odds of being culture-positive, with one farm having considerably greater odds than the remaining ones. …”
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Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring by XingTao Ren, XingTao Ren, Yan Ma, YiXin Zhou, YiXin Zhou

“…Future work may focus on further optimizing the retrieval algorithms and expanding the range of supported data platforms to enhance the robustness and scalability of the system.…”
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Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…In contrast, nuclear magnetic resonance (NMR) measurements, which provide information on pore body size distribution, are faster and can be leveraged to estimate capillary pressure using machine learning algorithms. Recently, artificial intelligence methods have also been applied to capillary pressure prediction (Qi et al., 2024).Currently, no readily applicable predictive model exists for estimating an entire capillary pressure curve directly from standard petrophysical logs and core data. …”
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Forestry climate adaptation with HarvesterSeasons service—a gradient boosting model to forecast soil water index SWI from a comprehensive set of predictors in Destination Earth by Mikko Strahlendorff, Anni Kröger, Golda Prakasam, Miriam Kosmale, Mikko Moisander, Heikki Ovaskainen, Asko Poikela

“…With this, the quality could also be demonstrated in the way our forestry climate service (HarvesterSeasons.com) would use the forecasts. …”
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