Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

“…Key water quality parameters—Sea Surface Temperature (SST), Total Suspended Solids (TSS), Turbidity, Salinity, and pH—were predicted through ML algorithms and interpolated using the Empirical Bayesian Kriging (EBK) model in ArcGIS Pro. …”
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Pharmacologic Disruption: How Emerging Weight Loss Therapies Are Challenging Bariatric Surgery Guidelines by Safi G. Alqatari, Abrar J. Alwaheed, Manal A. Hasan, Reem J. Al Argan, Marj M. Alabdullah, Mohammed D. Al Shubbar

“…In this narrative review, we examine the evolution of surgical eligibility thresholds and critically assess the potential role of novel pharmacotherapies in redefining treatment algorithms. By comparing the efficacy, safety, metabolic benefits, and cost-effectiveness of surgery versus next-generation drugs, we explore whether a more stepwise, pharmacotherapy-first approach may now be justified, particularly in patients with BMI 30–40 kg/m². …”
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Application of machine learning in assessing disease activity in SLE by Feng Wang, Ting Wang, Wei Wei, Yun Wang, Renren Ouyang, Rujia Chen, Hongyan Hou, Shiji Wu, Peihong Yuan

“…Multiple machine learning algorithms were employed to construct models for assessing SLE disease activity.Results The patients were divided into two cohorts, cohort 1 used as the training set to build the machine learning models and cohort 2 for external validation. …”
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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…Nonetheless, after this timeframe concludes, a large number of owners turn to unapproved service providers, mainly motivated by financial factors. This change signifies a significant drop in income for automakers and their certified service networks. …”
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Comparison of in Situ Plant Area Index and Remotely Sensed Leaf Area Index of Northeastern American Deciduous, Mixed, and Coniferous Forests for SMAPVEX19-22 by Christopher L. Cook, Laura Bourgeau-Chavez, Dorthea Vander Bilt, Mary Ellen Miller, Simon Kraatz, Michael H. Cosh, Victoria R. Kelly, Andreas Colliander

“…Smaller <italic>y</italic>-intercept values (&lt; -0.56) associated with the higher resolution products relative to the coarse resolution products (&gt; -0.29) could indicate greater influence of woody biomass on higher resolution RS LAI algorithms relative to low resolution RS LAI algorithms. …”
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Research Progress on Information Model of Urban Green Space by Wei ZHANG, Yahan YAN

“…Algorithms for constructing three-dimensional plant models include L-system algorithms and various neural networks, which can assist in generating 3D models. …”
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Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Int... by Min-Young Yu, Hae Young Yoo, Ga In Han, Eun-Jung Kim, Youn-Jung Son

“… Abstract BackgroundMachine learning (ML) models may offer greater clinical utility than conventional risk scores, such as the Thrombolysis in Myocardial Infarction (TIMI) and Global Registry of Acute Coronary Events (GRACE) risk scores. …”
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Open real-time, non-invasive fish detection and size estimation utilizing binocular camera system in a Portuguese river affected by hydropeaking by Jürgen Soom, Isabel Boavida, Renan Leite, Maria João Costa, Gert Toming, Mairo Leier, Jeffrey A. Tuhtan

“…Results indicate that hydropeaking strongly influences how fish may use instream flow refuges during hydropeaking. …”
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Quantitative image analysis of the extracellular matrix of esophageal squamous cell carcinoma and high grade dysplasia via two-photon microscopy by Kausalya Neelavara Makkithaya, Wei-Chung Chen, Chun-Chieh Wu, Ming-Chi Chen, Wei-Hsun Wang, Jackson Rodrigues, Ming-Tsang Wu, Nirmal Mazumder, I-Chen Wu, Guan-Yu Zhuo

“…Thus, distinguishing between the two may require careful examination by a pathologist and consideration of clinical findings. …”
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Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets by Catarina Lopes, Andreia Brandão, Manuel R. Teixeira, Mário Dinis-Ribeiro, Carina Pereira

“…Leveraging transcriptomic data from the Gene Expression Omnibus (GEO), we constructed and validated predictive models through machine learning algorithms within the tidymodels framework. Tissue-based models were validated on independent tissue datasets, and subsequently applied to saliva. …”
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Validating laboratory predictions of soil rewetting respiration pulses using field data by X. Li, X. Li, M. Pallandt, M. Pallandt, D. Naidu, D. Naidu, J. Rousk, G. Hugelius, G. Hugelius, S. Manzoni, S. Manzoni

“…<p>Improved understanding of the mechanisms driving heterotrophic CO<span class="inline-formula">₂</span> emissions after rewetting of a dry soil may improve projections of future soil carbon fate. …”
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Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool by Hatem Ali, Arun Shroff, Tibor Fülöp, Miklos Z. Molnar, Adnan Sharif, Bernard Burke, Sunil Shroff, David Briggs, Nithya Krishnan

“…We set out to apply artificial intelligence (AI) algorithms to create a highly predictive risk stratification indicator, applicable to the UK’s transplant selection process.Methodology: Pre-transplant characteristics from 12,661 live-donor kidney transplants (performed between 2007 and 2022) from the United Kingdom Transplant Registry database were analyzed. …”
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Anti-masking Posts on Instagram: Content Analysis During the COVID-19 Pandemic by Emma K. Quinn, Robert T. Duffy, Kristian Larsen, Maria Dalton, Cheryl E. Peters

“…Social media algorithms promote similar misinformation or authority-questioning beliefs to users who view related content. …”
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Explainable machine learning model for predicting compressive strength of CO2-cured concrete by Jia Chu, Bingbing Guo, Taotao Zhong, Qinghao Guan, Yan Wang, Ditao Niu

“…However, higher CO2 pressures may decrease the strength due to the increased risk of microcrack propagation caused by the synergistic effects of excessive pressure and considerable heat from the carbonation reaction.…”
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THEMIS: A Parameter Estimation Framework for the Event Horizon Telescope by Avery E. Broderick, Roman Gold, Mansour Karami, Jorge A. Preciado-López, Paul Tiede, Hung-Yi Pu, Kazunori Akiyama, Antxon Alberdi, Walter Alef, Keiichi Asada, Rebecca Azulay, Anne-Kathrin Baczko, Mislav Baloković, John Barrett, Dan Bintley, Lindy Blackburn, Wilfred Boland, Katherine L. Bouman, Geoffrey C. Bower, Michael Bremer, Christiaan D. Brinkerink, Roger Brissenden, Silke Britzen, Dominique Broguiere, Thomas Bronzwaer, Do-Young Byun, John E. Carlstrom, Andrew Chael, Shami Chatterjee, Koushik Chatterjee, Ming-Tang Chen, Yongjun Chen, Ilje Cho, John E. Conway, James M. Cordes, Geoffrey B. Crew, Yuzhu Cui, Jordy Davelaar, Mariafelicia De Laurentis, Roger Deane, Jessica Dempsey, Gregory Desvignes, Sheperd S. Doeleman, Ralph P. Eatough, Heino Falcke, Vincent L. Fish, Ed Fomalont, Raquel Fraga-Encinas, Per Friberg, Christian M. Fromm, Peter Galison, Charles F. Gammie, Roberto García, Olivier Gentaz, Boris Georgiev, Ciriaco Goddi, José L. Gómez, Minfeng Gu, Mark Gurwell, Kazuhiro Hada, Michael H. Hecht, Ronald Hesper, Luis C. Ho, Paul Ho, Mareki Honma, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Makoto Inoue, Sara Issaoun, David J. James, Michael Janssen, Britton Jeter, Wu Jiang, Alejandra Jiménez-Rosales, Michael D. Johnson, Svetlana Jorstad, Taehyun Jung, Ramesh Karuppusamy, Tomohisa Kawashima, Garrett K. Keating, Mark Kettenis, Jae-Young Kim, Jongsoo Kim, Motoki Kino, Jun Yi Koay, Patrick M. Koch, Shoko Koyama, Michael Kramer, Carsten Kramer, Thomas P. Krichbaum, Cheng-Yu Kuo, Sang-Sung Lee, Yan-Rong Li, Zhiyuan Li, Michael Lindqvist, Rocco Lico, Kuo Liu, Elisabetta Liuzzo, Wen-Ping Lo, Andrei P. Lobanov, Laurent Loinard, Colin Lonsdale, Ru-Sen Lu, Nicholas R. MacDonald, Jirong Mao, Alan P. Marscher, Iván Martí-Vidal, Satoki Matsushita, Lynn D. Matthews, Karl M. Menten, Yosuke Mizuno, Izumi Mizuno, James M. Moran, Kotaro Moriyama, Monika Moscibrodzka, Cornelia Müller, Hiroshi Nagai, Neil M. Nagar, Masanori Nakamura, Ramesh Narayan, Gopal Narayanan, Iniyan Natarajan, Roberto Neri, Chunchong Ni, Aristeidis Noutsos, Hiroki Okino, Héctor Olivares, Gisela N. Ortiz-León, Tomoaki Oyama, Daniel C. M. Palumbo, Jongho Park, Ue-Li Pen, Dominic W. Pesce, Vincent Piétu, Richard Plambeck, Aleksandar PopStefanija, Oliver Porth, Ben Prather, Venkatessh Ramakrishnan, Ramprasad Rao, Mark G. Rawlings, Alexander W. Raymond, Luciano Rezzolla, Bart Ripperda, Freek Roelofs, Alan Rogers, Eduardo Ros, Mel Rose, Helge Rottmann, Chet Ruszczyk, Benjamin R. Ryan, Kazi L. J. Rygl, Salvador Sánchez, David Sánchez-Arguelles, Mahito Sasada, Tuomas Savolainen, F. Peter Schloerb, Karl-Friedrich Schuster, Lijing Shao, Zhiqiang Shen, Des Small, Bong Won Sohn, Jason SooHoo, Fumie Tazaki, Remo P. J. Tilanus, Michael Titus, Kenji Toma, Pablo Torne, Efthalia Traianou, Sascha Trippe, Shuichiro Tsuda, Ilse van Bemmel, Huib Jan van Langevelde, Daniel R. van Rossum, Jan Wagner, John Wardle, Jonathan Weintroub, Norbert Wex, Robert Wharton, Maciek Wielgus, George N. Wong, Qingwen Wu, Doosoo Yoon, André Young, Ken Young, Ziri Younsi, Feng Yuan, Ye-Fei Yuan, J. Anton Zensus, Guangyao Zhao, Shan-Shan Zhao, Ziyan Zhu, The Event Horizon Telescope Collaboration

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Heart failure with preserved left ventricular ejection fraction – clinical perspectives by Małgorzata Niemiec, Bartosz Gruchlik, Nicola Dyrek, Jan Niemiec, Bartosz Basiaga, Krzysztof Bednarz, Dorota Piłat, Kinga Czepczor, Maciej Podolski, Katarzyna Mizia-Stec

“…Until recently, HFpEF treatment focused mainly on symptom relief and comorbidity management. …”
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A new 3D vision-based leaf rolling index (LRI) and its application as a stable indicator of cotton drought stress by Hangxing Huang, Jian Kang, Jinliang Chen, Risheng Ding, Hongna Lu, Siyu Wu, Shaozhong Kang

“…This study demonstrates that LRI based on 3D vision in cotton may serve as a reliable morphological indicator for indicating drought stress and evaluating photosynthetic efficiency.…”
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New Insights into the Role of the Immune Microenvironment in Breast Carcinoma by Luis de la Cruz-Merino, Antonio Barco-Sánchez, Fernando Henao Carrasco, Esteban Nogales Fernández, Ana Vallejo Benítez, Javier Brugal Molina, Antonio Martínez Peinado, Ana Grueso López, Manuel Ruiz Borrego, Manuel Codes Manuel de Villena, Víctor Sánchez-Margalet, Adoración Nieto-García, Emilio Alba Conejo, Noelia Casares Lagar, José Ibáñez Martínez

“…Infiltration by tumor infiltrating lymphocytes (TIL) and their subtypes, tumor-associated macrophages (TAM) and myeloid-derived suppressive cells (MDSC) seem bona fide prognostic and even predictive biomarkers, that will eventually be incorporated into diagnostic and therapeutic algorithms of breast cancer. In addition, the complex interaction of costimulatory and coinhibitory molecules on the immune synapse and the different signals that they may exert represent another exciting field to explore. …”
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Predicting postoperative trauma-induced coagulopathy in patients with severe injuries by machine learning by Xiaohui Du, Wei Wang, Bo Xu, Jiang Zheng, Victor W. Xia, Yi Guo, Shuai Feng, Qingxiang Mao, Hong Fu

“…Utilizing machine learning may enhance clinical decision-making and improve management strategies for postoperative coagulation issues.…”
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An MRI-based fusion model for preoperative prediction of perineural invasion status in patients with intrahepatic cholangiocarcinoma by Zuochao Qi, Hao Yuan, Qingshan Li, Pengyu Chen, Dongxiao Li, Kunlun Chen, Bo Meng, Peigang Ning, Haibo Yu, Deyu Li

“…Feature selection was performed, and a radiomics model was constructed using machine learning algorithms, followed by SHapley Additive exPlanations (SHAP) visualization. …”
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