• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 145 matches

• 2025
• 
  Ji Wang, Zhaoqing Liu, Yujie Liu, Lin Li, Lingyu Shao, Xiao Zhang, Shuyan Li, Boming Song:
  Deep Learning-Based Response-to-Name Detection: Empirical Study on Early Screening of Autism Spectrum Disorder in Children. IEEE Access 13: 81406-81416 (2025)
• 
  Blanca Maria Priego Torres, Daniel Sánchez Morillo, Ebrahim Khalili, Miguel Ángel Conde-Sánchez, Andrés García-Gámez, Antonio León Jiménez:
  Automated engineered-stone silicosis screening and staging using Deep Learning with X-rays. Comput. Biol. Medicine 191: 110153 (2025)
• 
  Tong Pan, Yue Bi, Xiaoyu Wang, Ying Zhang, Geoffrey I. Webb, Robin B. Gasser, Lukasz A. Kurgan, Jiangning Song:
  SCREEN: A Graph-based Contrastive Learning Tool to Infer Catalytic Residues and Assess Enzyme Mutations. Genom. Proteom. Bioinform. 22(6) (2025)
• 
  Haomin Li, Siyuan Gao, Dan Wu, Min Zhu, Zhenzhen Hu, Kexin Fang, Xiuru Chen, Zhou Ni, Jing Li, Beibei Zhao, Xuhui She, Xinwen Huang:
  Training machine learning models to detect rare inborn errors of metabolism (IEMs) based on GC-MS urinary metabolomics for diseases screening. Int. J. Medical Informatics 195: 105765 (2025)
• 
  Kellen Sharp, Rachel R. Ouellette, Rujula Singh Rajendra Singh, Elise E. DeVito, Neil Kamdar, Amanda de la Noval, Dhiraj Murthy, Grace Kong:
  Generative artificial intelligence and machine learning methods to screen social media content. PeerJ Comput. Sci. 11: e2710 (2025)
• 
  Nicolò Bellarmino, Riccardo Cantoro, Martin Huch, Tobias Kilian, Ulf Schlichtmann, Giovanni Squillero:
  Deep Learning Strategies for Labeling and Accuracy Optimization in Microcontroller Performance Screening. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 44(2): 641-654 (2025)
• 
  Chong Zhong, Yang Li, Jinfeng Xu, Xiang Fu, Yunhao Liu, Qiuyi Huang, Danjuan Yang, Meiyan Li, Aiyi Liu, Alan H. Welsh, Xingtao Zhou, Bo Fu, Catherine C. Liu:
  CeViT: Copula-Enhanced Vision Transformer in multi-task learning and bi-group image covariates with an application to myopia screening. CoRR abs/2501.06540 (2025)
• 
  Shramana Dey, Pallabi Dutta, Riddhasree Bhattacharyya, Surochita Pal, Sushmita Mitra, Rajiv Raman:
  Adaptive Class Learning to Screen Diabetic Disorders in Fundus Images of Eye. CoRR abs/2501.12048 (2025)
• 2024
• 
  Viet-Khoa Tran-Nguyen, Anne-Claude Camproux, Olivier Taboureau:
  ClassyPose: A Machine-Learning Classification Model for Ligand Pose Selection Applied to Virtual Screening in Drug Discovery. Adv. Intell. Syst. 6(12) (2024)
• 
  Félix Nieto-del-Amor, Yiyao Ye-Lin, Rogelio Monfort-Ortiz, Vicente Jose Diago-Almela, Fernando Modrego-Pardo, Jose L. Martinez-de-Juan, Dongmei Hao, Gema Prats-Boluda:
  Automatic semantic segmentation of EHG recordings by deep learning: An approach to a screening tool for use in clinical practice. Comput. Methods Programs Biomed. 254: 108317 (2024)
• 
  Taw Kuei Chan:
  Implementing chroma key compositing with a green screen to improve the learning experience of remote students during synchronous hybrid lectures. Educ. Inf. Technol. 29(12): 14687-14713 (2024)
• 
  Meryem Altin Karagöz, Özkan Ufuk Nalbantoglu, Dervis Karaboga, Bahriye Akay, Alper Bastürk, Halil Ulutabanca, Serap Dogan, Damla Coskun, Osman Demir:
  Deep learning-based breast cancer diagnosis with multiview of mammography screening to reduce false positive recall rate. Turkish J. Electr. Eng. Comput. Sci. 32(3): 382-402 (2024)
• 
  Meng Ting Hou, Juan Bao, Shu Xiong Zheng, Si Tong Li, Xi Yu Li:
  Bioinformatics and Machine Learning-Based Screening of Key Genes in Alzheimer's Disease. Int. J. Web Serv. Res. 21(1): 1-17 (2024)
• 
  Cheng Liu, Yi Shi, Wenjing Xie, Xinzhong Bao:
  A novel approach to screening patents for securitization: a machine learning-based predictive analysis of high-quality basic asset. Kybernetes 53(2): 763-778 (2024)
• 
  Ruoyu Chen, Weiyi Zhang, Fan Song, Honghua Yu, Dan Cao, Yingfeng Zheng, Mingguang He, Danli Shi:
  Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening. npj Digit. Medicine 7(1) (2024)
• 
  Tianhong Quan, Ye Yuan, Yu Luo, Youyi Song, Teng Zhou, Jiaqi Wang:
  From Regression to Classification: Fuzzy Multikernel Subspace Learning for Robust Prediction and Drug Screening. IEEE Trans. Ind. Informatics 20(3): 4137-4148 (2024)
• 
  Anton Nailevich Gafurov, Daehyeon Kim, Yuchang Choi, Hyejin Park, Inyoung Kim, Dongho Oh, Taik-Min Lee:
  Machine Direction Registration Modelling in Roll-to-Roll Screen Printing by Deep Learning. AMC 2024: 1-6
• 
  Zejun Ye, Defeng Zhao, Wentao Zhang, Ruixuan Wang:
  CtF: Mitigating Visual Confusion in Continual Learning Through a Coarse-To-Fine Screening. ICIC (6) 2024: 134-146
• 
  Shramana Dey, Pallabi Dutta, Riddhasree Bhattacharyya, Surochita Pal Das, Sushmita Mitra, Rajiv Raman:
  Adaptive Class Learning to Screen Diabetic Disorders in Fundus Images of Eye. ICPR (28) 2024: 124-137
• 
  C. W. Lin, P. C. Tsao, Y. L. Yang, C. C. Sun, C. C. Huang, C. W. Chen, C. K. Chang, Y. J. Ting, K. Koh, Ross Lee, W. C. Chen, Y. S. Huang, M. Z. Lee, C. T. Lai, T. H. Lee:
  Utilizing Transformer Deep Learning Based Outlier Detection to Screen Out Reliability Weak ICs. IRPS 2024: 1-5
• 
  Fatemah Faraji, Gokhan Bilgin:
  Deep Learning Approach to Improve Breast CancerClassification for Screening Mammography. SIU 2024: 1-4
• 
  Danny Falero, Muhammad Ashad Kabir, Nusrat Homaira:
  From Lab to Pocket: A Novel Continual Learning-based Mobile Application for Screening COVID-19. CoRR abs/2410.12589 (2024)
• 2023
• 
  Linda Greta Dui:
  Novel ICT solutions to support the early screening of specific learning disabilities and the characterization of handwriting evolution. Polytechnic University of Milan, Italy, 2023
• 
  Ryan G. L. Koh, Md. Asif Khan, Sajjad Rashidiani, Samah Hassan, Victoria Tucci, Theodore Liu, Karlo Nesovic, Dinesh Kumbhare, Thomas E. Doyle:
  Check It Before You Wreck It: A Guide to STAR-ML for Screening Machine Learning Reporting in Research. IEEE Access 11: 101567-101579 (2023)
• 
  Peng Jiang, Xuekong Li, Hui Shen, Yuqi Chen, Lang Wang, Hua Chen, Jing Feng, Juan Liu:
  A systematic review of deep learning-based cervical cytology screening: from cell identification to whole slide image analysis. Artif. Intell. Rev. 56(S2): 2687-2758 (2023)
• 
  Teresa Gonçalves, Rute Veladas, Hua Yang, Renata Vieira, Paulo Quaresma, Paulo Infante, Cátia Sousa Pinto, João Oliveira, Maria Cortes Ferreira, Jéssica Morais, Ana Raquel Pereira, Nuno Fernandes, Carolina Gonçalves:
  Clinical Screening Prediction in the Portuguese National Health Service: Data Analysis, Machine Learning Models, Explainability and Meta-Evaluation. Future Internet 15(1): 26 (2023)
• 
  Zhenrun Zhan, Pengyong Han, Xu Tang, Jinpeng Yang, Xiaodan Bi, Tingting Zhao:
  Applying machine learning to screen for acute myocardial infarction-related biomarkers and immune infiltration features and validate it clinically and experimentally. Int. J. Imaging Syst. Technol. 33(6): 2023-2043 (2023)
• 
  Thomas E. Hadfield, Jack Scantlebury, Charlotte M. Deane:
  Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding. J. Cheminformatics 15(1): 84 (2023)
• 
  Anna M. Díaz-Rovira, Helena Martín, Thijs Beuming, Lucía Díaz, Victor Guallar, Soumya S. Ray:
  Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures. J. Chem. Inf. Model. 63(6): 1668-1674 (2023)
• 
  Toni Sivula, Laxman Yetukuri, Tuomo Kalliokoski, Heikki Käsnänen, Antti Poso, Ina Pöhner:
  Machine Learning-Boosted Docking Enables the Efficient Structure-Based Virtual Screening of Giga-Scale Enumerated Chemical Libraries. J. Chem. Inf. Model. 63(18): 5773-5783 (2023)

skipping 115 more matches