Low-dimensional multiscale fast SAR image registration method by Jiamu Li, Wenbo Yu, Zijian Wang, Jiaxin Xie, Xiaojie Zhou, Yabo Liu, Zhongjun Yu, Meng Li, Yi Wang

“…Note that we condense the feature information of candidate points in the whole neighbourhood in an intensity-order way, which significantly reduces the dimensionality of the descriptors. …”
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Multi-task aquatic toxicity prediction model based on multi-level features fusion by Xin Yang, Jianqiang Sun, Bingyu Jin, Yuer Lu, Jinyan Cheng, Jiaju Jiang, Qi Zhao, Jianwei Shuai

“…Furthermore, in comparison with previous algorithms, ATFPGT-multi outperforms comparative methods, emphasizing that our approach exhibits higher accuracy and reliability in predicting aquatic toxicity. …”
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Global trends in the use of artificial intelligence for urological tumor histopathology: A 20-year bibliometric analysis by Fazhong Dai, Yifeng He, Juan Duan, Kangjian Lin, Qian Lv, Zhongxiang Zhao, Yesong Zou, Jianhong Jiang, Zongtai Zheng, Xiaofu Qiu

“…Prioritizing standardized data protocols, fairness-aware algorithms, and dynamic regulatory guidelines will be essential to ensure equitable, reliable, and clinically actionable AI solutions, ultimately advancing precision oncology in urological malignancies.…”
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Comparative assessment of line probe assays and targeted next-generation sequencing in drug-resistant tuberculosis diagnosisResearch in context by Giovanna Carpi, Marva Seifert, Andres De la Rossa, Swapna Uplekar, Camilla Rodrigues, Nestani Tukvadze, Shaheed V. Omar, Anita Suresh, Timothy C. Rodwell, Rebecca E. Colman

“…Interpretation: LPAs demonstrated lower sensitivity and more limited drug resistance detection compared to tNGS workflows, underscoring the advantages of tNGS for improving DR-TB diagnostic algorithms. These findings provide critical evidence to guide updates in DR-TB diagnostic programs. …”
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Using machine learning for mortality prediction and risk stratification in atezolizumab‐treated cancer patients: Integrative analysis of eight clinical trials by Yougen Wu, Wenyu Zhu, Jing Wang, Lvwen Liu, Wei Zhang, Yang Wang, Jindong Shi, Ju Xia, Yuting Gu, Qingqing Qian, Yang Hong

“…Machine‐learning algorithms (extreme gradient boosting, random forest, logistic regression with lasso regularization, support vector machine, and K‐nearest neighbor) were applied to develop prediction models. …”
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Research Progress of Intelligent Evaluation and Virtual Reality Based Training in Upper Limb Rehabilitation afrer Stroke by XIE Qiurong, LIN Wanqi, ZHANG Qi, SHENG Bo, ZHANG Yanxin, HUANG Jia

“…Automated assessment of upper extremity motor function based on machine learning algorithms with markerless sensing techniques has focused on the Fugl-Meyer assessment of upper extremity (FMA-UE), Brunnstrom stages, and Wolf motor function test (WMFT) scales and has been proved with high-scoring accuracy and time efficiency. …”
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System architecture and key technologies of intelligent, safe and efficient mining for rockburst coal seams by Zhigang DENG, Yunpeng LI, Shankun ZHAO, Yin WANG, Shaogang LI, Linghai KONG, Junjun JIANG, Zhenguo SU, Yizhe LI, Kai QIN

“…First of all, digital twin technology is used to build a fine digital model, deeply detect and analyze the geological structure of the area where the mine is located, accurately measure the characteristics of the regional geostress field and the physical and mechanical properties of coal and rock, and rely on advanced algorithms to carry out engineering distribution of formation change information to achieve “transparency” of geological information. …”
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Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review by Kapongo D. Lumamba, Gordon Wells, Delon Naicker, Threnesan Naidoo, Adrie J. C. Steyn, Mandlenkosi Gwetu

“…The ultimate goal is to promote the development of more efficient and accurate algorithms for the detection or analysis of TB, and raise awareness about the importance of early detection. …”
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Cancer phylogenetic tree inference at scale from 1000s of single cell genomes by Salehi, Sohrab, Dorri, Fatemeh, Chern, Kevin, Kabeer, Farhia, Rusk, Nicole, Funnell, Tyler, Williams, Marc J., Lai, Daniel, Andronescu, Mirela, Campbell, Kieran R., McPherson, Andrew, Aparicio, Samuel, Roth, Andrew, Shah, Sohrab P., Bouchard-Côté, Alexandre

“…A new generation of scalable single cell whole genome sequencing (scWGS) methods allows unprecedented high resolution measurement of the evolutionary dynamics of cancer cell populations. …”
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Orchard-Wide Visual Perception and Autonomous Operation of Fruit Picking Robots: A Review by CHEN Mingyou, LUO Lufeng, LIU Wei, WEI Huiling, WANG Jinhai, LU Qinghua, LUO Shaoming

“…This includes not only the latest advancements in devising movement paths for robot mobility but also adaptive strategies that allow robots to react to unexpected obstacles or changes within the whole environment. Enhanced strategies for effective fruit picking using the Eye-in-Hand system involve the development of more dexterous robotic hands and improved algorithms for precisely predicting the optimal picking point of each fruit. …”
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The pre- and post-COVID-19 pandemic dengue fever patterns in southeastern coastal China in 2019 and 2024: molecular evolution and strain replacement by Tianran Zhang, Yaqi Shi, Leyi Zhang, Jian Wang, Chengchao Yu, Binbin Lv, Sisi Wu, Yiru Huang, Xuewei Liu, Hupiao Dai, Mingshi Zhou, Yanjuan Liao, Wei Wang, Guankai Lin

“…Recombination was analyzed using seven detection algorithms implemented in RDP4. Hamming distances were used to profile amino acid substitutions. …”
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Application of hyperthermia robots in Cyber-syndrome treatment by Xueyan YIN, Feifei SHI, Jinqiang WANG, Huansheng NING

“…Compared with domestic research, foreign research in this area is scarcer, but the field as a whole shows a good development trend and broad application prospects. …”
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Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinomaResearch in context by Bolin Song, Amaury Leroy, Kailin Yang, Tanmoy Dam, Xiangxue Wang, Himanshu Maurya, Tilak Pathak, Jonathan Lee, Sarah Stock, Xiao T. Li, Pingfu Fu, Cheng Lu, Paula Toro, Deborah J. Chute, Shlomo Koyfman, Nabil F. Saba, Mihir R. Patel, Anant Madabhushi

“…SMuRF integrates features from CT corresponding to the PT and LN, as well as whole slide pathology images from the PT as a predictor of survival and tumour grade in HPV-associated OPSCC. …”
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Multiple loci are associated with white blood cell phenotypes. by Michael A Nalls, David J Couper, Toshiko Tanaka, Frank J A van Rooij, Ming-Huei Chen, Albert V Smith, Daniela Toniolo, Neil A Zakai, Qiong Yang, Andreas Greinacher, Andrew R Wood, Melissa Garcia, Paolo Gasparini, Yongmei Liu, Thomas Lumley, Aaron R Folsom, Alex P Reiner, Christian Gieger, Vasiliki Lagou, Janine F Felix, Henry Völzke, Natalia A Gouskova, Alessandro Biffi, Angela Döring, Uwe Völker, Sean Chong, Kerri L Wiggins, Augusto Rendon, Abbas Dehghan, Matt Moore, Kent Taylor, James G Wilson, Guillaume Lettre, Albert Hofman, Joshua C Bis, Nicola Pirastu, Caroline S Fox, Christa Meisinger, Jennifer Sambrook, Sampath Arepalli, Matthias Nauck, Holger Prokisch, Jonathan Stephens, Nicole L Glazer, L Adrienne Cupples, Yukinori Okada, Atsushi Takahashi, Yoichiro Kamatani, Koichi Matsuda, Tatsuhiko Tsunoda, Toshihiro Tanaka, Michiaki Kubo, Yusuke Nakamura, Kazuhiko Yamamoto, Naoyuki Kamatani, Michael Stumvoll, Anke Tönjes, Inga Prokopenko, Thomas Illig, Kushang V Patel, Stephen F Garner, Brigitte Kuhnel, Massimo Mangino, Ben A Oostra, Swee Lay Thein, Josef Coresh, H-Erich Wichmann, Stephan Menzel, JingPing Lin, Giorgio Pistis, André G Uitterlinden, Tim D Spector, Alexander Teumer, Gudny Eiriksdottir, Vilmundur Gudnason, Stefania Bandinelli, Timothy M Frayling, Aravinda Chakravarti, Cornelia M van Duijn, David Melzer, Willem H Ouwehand, Daniel Levy, Eric Boerwinkle, Andrew B Singleton, Dena G Hernandez, Dan L Longo, Nicole Soranzo, Jacqueline C M Witteman, Bruce M Psaty, Luigi Ferrucci, Tamara B Harris, Christopher J O'Donnell, Santhi K Ganesh

“…We implemented gene-clustering algorithms to evaluate functional connectivity among implicated loci and showed functional relationships across cell types. …”
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Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens by Paul English, Muir J. Morrison, Blaine Mathison, Elizabeth Enrico, Ryan Shean, Brendan O'Fallon, Deven Rupp, Katie Knight, Alexandra Rangel, Jeffrey Gilivary, Amanda Vance, Haleina Hatch, Leo Lin, David P. Ng, Salika M. Shakir

“…Following acid-fast staining, whole slide images (WSI) were digitized, and AFB organisms were manually annotated. …”
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Habitat radiomics analysis for progression free survival and immune-related adverse reaction prediction in non-small cell lung cancer treated by immunotherapy by Yuemin Wu, Wei Zhang, Xiao Liang, Pengpeng Zhang, Mengzhe Zhang, Yuqin Jiang, Yanan Cui, Yi Chen, Wenxin Zhou, Qi Liang, Jiali Dai, Chen Zhang, Jiali Xu, Jun Li, Tongfu Yu, Zhihong Zhang, Renhua Guo

“…This model outperformed both the Whole-tumor Radiomics Signature model (AUCs of 0.870, 0.736, and 0.626) and the Habitat Signature model (AUCs of 0.900, 0.804, and 0.808). …”
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Re-resection of brain metastases – outcomes of an institutional cohort study and literature review by David Wasilewski, Zoe Shaked, Annalena Fuchs, Siyer Roohani, Ran Xu, Max Schlaak, Nikolaj Frost, Martin Misch, David Capper, David Kaul, Julia Onken, Peter Vajkoczy, Felix Ehret

“…Further research to improve patient selection and treatment algorithms is warranted.…”
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A Hierarchical Machine Learning-Based Strategy for Mapping Grassland in Manitoba’s Diverse Ecoregions by Mirmajid Mousavi, James Kobina Mensah Biney, Barbara Kishchuk, Ali Youssef, Marcos R. C. Cordeiro, Glenn Friesen, Douglas Cattani, Mustapha Namous, Nasem Badreldin

“…This study developed a novel pixel-based grassland classification approach using three supervised machine learning (ML) algorithms, which were assessed in the province of Manitoba, Canada. …”
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Functional Connectivity Changes in Primary Motor Cortex Subregions of Patients With Obstructive Sleep Apnea by Lifeng Li, Qimeng Shi, Bowen Fang, Yuting Liu, Xiang Liu, Yongqiang Shu, Yingke Deng, Yumeng Liu, Haijun Li, Junjie Zhou, Dechang Peng

“…Additionally, we employed three machine learning algorithms—support vector machine (SVM), random forest (RF), and logistic regression (LR)—to distinguish patients with OSA from HC based on FC features. …”
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Early Detection of Soil Salinization by Means of Spaceborne Hyperspectral Imagery by Giacomo Lazzeri, Robert Milewski, Saskia Foerster, Sandro Moretti, Sabine Chabrillat

“…Both datasets were pre-processed with multiple data transformation algorithms and 2D correlograms, PLSR and the Random Forest regressor were tested to identify the best model for salinity detection. …”
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