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检索条件"机构=Biomedical Data Science and Machine Learning Group"
283 条 记 录,以下是161-170 订阅
排序:
Occam's razor for AI: Coarse-graining Hammett Inspired Product Ansatz in Chemical Space
arXiv
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arXiv 2023年
作者: Bragato, Marco Von Rudorff, Guido Falk Von Lilienfeld, O. Anatole University of Vienna Faculty of Physics Kolingasse 1416 WienAT1090 Austria University Kassel Department of Chemistry Heinrich-Plett-Str.40 Kassel34132 Germany Heinrich-Plett-Straße 40 Kassel34132 Germany Vector Institute for Artificial Intelligence TorontoONM5S 1M1 Canada Departments of Chemistry Materials Science and Engineering and Physics University of Toronto St. George Campus TorontoON Canada Machine Learning Group Technische Universität Berlin Germany Berlin Institute for the Foundations of Learning and Data Berlin10587 Germany
data-hungry machine learning methods have become a new standard to efficiently navigate chemical compound space for molecular and materials design and discovery. Due to the severe scarcity and cost of high-quality exp... 详细信息
来源: 评论
Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images
arXiv
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arXiv 2022年
作者: Yeung, Pak-Hei Aliasi, Moska Haak, Monique Xie, Weidi Namburete, Ana I.L. Oxford Machine Learning in NeuroImaging Lab Department of Computer Science University of Oxford Oxford United Kingdom Department of Engineering Science Institute of Biomedical Engineering University of Oxford Oxford United Kingdom Division of Fetal Medicine Department of Obstetrics Leiden University Medical Center Leiden2333 ZA Netherlands Shanghai Jiao Tong University Shanghai China Visual Geometry Group Department of Engineering Science University of Oxford Oxford United Kingdom
Two-dimensional (2D) freehand ultrasound is the mainstay in prenatal care and fetal growth monitoring. The task of matching corresponding cross-sectional planes in the 3D anatomy for a given 2D ultrasound brain scan i... 详细信息
来源: 评论
Towards self-driving laboratories: The central role of density functional theory in the AI age
arXiv
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arXiv 2023年
作者: Huang, Bing von Rudorff, Guido Falk Anatole von Lilienfeld, O. University of Vienna Faculty of Physics Kolingasse 14-16 WienAT1090 Austria University Kassel Department of Chemistry Heinrich-Plett-Str.40 Kassel34132 Germany Heinrich-Plett-Straße 40 Kassel34132 Germany Vector Institute for Artificial Intelligence TorontoONM5S 1M1 Canada Department of Chemistry Materials Science and Engineering and Physics University of Toronto St. George Campus TorontoON Canada Machine Learning Group Technische Universität Berlin Berlin Institute for the Foundations of Learning and Data Berlin10587 Germany
Density functional theory (DFT) plays a pivotal role for the chemical and materials science due to its relatively high predictive power, applicability, versatility and computational efficiency. We review recent progre... 详细信息
来源: 评论
Latent space conditioning on generative adversarial networks
arXiv
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arXiv 2020年
作者: Lopez, Ricard Durall Ho, Kalun Pfreundt, Franz-Josef Keuper, Janis Fraunhofer ITWM Germany IWR University of Heidelberg Germany Fraunhofer Center Machine Learning Germany Data and Web Science Group University of Mannheim Germany Institute for Machine Learning and Analytics Offenburg University Germany
Generative adversarial networks are the state of the art approach towards learned synthetic image generation. Although early successes were mostly unsupervised, bit by bit, this trend has been superseded by approaches... 详细信息
来源: 评论
Accurate machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations
arXiv
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arXiv 2022年
作者: Unke, Oliver T. Stöhr, Martin Ganscha, Stefan Unterthiner, Thomas Maennel, Hartmut Kashubin, Sergii Ahlin, Daniel Gastegger, Michael Sandonas, Leonardo Medrano Tkatchenko, Alexandre Müller, Klaus-Robert Google Research Brain Team Machine Learning Group Technische Universität Berlin Berlin10587 Germany Technische Universität Berlin Berlin10623 Germany Department of Physics and Materials Science University of Luxembourg Luxembourg CityL-1511 Luxembourg BASLEARN TU Berlin Berlin10587 Germany BASF Joint Lab for Machine Learning Technische Universität Berlin Berlin10587 Germany Department of Artificial Intelligence Korea University Anam-dong Seongbuk-gu Seoul02841 Korea Republic of Max Planck Institute for Informatics Stuhlsatzenhausweg Saarbrücken66123 Germany BIFOLD Berlin Institute for the Foundations of Learning and Data Berlin Germany
Molecular dynamics (MD) simulations allow atomistic insights into chemical and biological processes. Accurate MD simulations require computationally demanding quantum-mechanical calculations, being practically limited... 详细信息
来源: 评论
Lung Ultrasound for the Detection of Pulmonary Tuberculosis Using Expert- and AI-Guided Interpretation: A Prospective Cohort Study
SSRN
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SSRN 2025年
作者: Suttels, Véronique Brokowski, Trevor Wachinou, Ablo Prudence Wolleb, Julia Hada, Aboudou Rasisou Du Toit, Jacques Daniel Fiogbé, Arnauld Attannon Guendehou, Brice Alovokpinhou, Frederic Sefou, Fadyl Makpemikpa, Ginette Bessat, Cécile Roux, Alexia Garcia, Elena Brahier, Thomas Opota, Onya Doenz, Jonathan Vignoud, Julien Agodokpessi, Gildas Affolabi, Dissou Hartley, Mary-Anne Boillat-Blanco, Noémie Department of Medicine Infectious Diseases Lausanne University Hospital University of Lausanne Lausanne Switzerland Yale School of Medicine Department of Biomedical Informatics & Data Science New HavenCT06510 United States Cotonou Benin Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa Emergency Department Lausanne University Hospital University of Lausanne Lausanne1011 Switzerland Institute of Microbiology University of Lausanne University Hospital Centre Lausanne Switzerland Lausanne1015 Switzerland National Reference Laboratory for Mycobacteriology Cotonou Benin Yale University United States Faculty of Health Sciences Benin Intelligent Global Health Machine Learning and Optimization Laboratory
Background: Point-of-care lung ultrasound (LUS) is a promising tool for portable sputum-free tuberculosis (TB) triage. We investigate the diagnostic performance of LUS to detect TB using expert and artificial intellig... 详细信息
来源: 评论
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
arXiv
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arXiv 2024年
作者: Bassi, Pedro R.A.S. Li, Wenxuan Tang, Yucheng Isensee, Fabian Wang, Zifu Chen, Jieneng Chou, Yu-Cheng Roy, Saikat Kirchhoff, Yannick Rokuss, Maximilian Huang, Ziyan Ye, Jin He, Junjun Wald, Tassilo Ulrich, Constantin Baumgartner, Michael Maier-Hein, Klaus H. Jaeger, Paul Ye, Yiwen Xie, Yutong Zhang, Jianpeng Chen, Ziyang Xia, Yong Xing, Zhaohu Zhu, Lei Sadegheih, Yousef Bozorgpour, Afshin Kumari, Pratibha Azad, Reza Merhof, Dorit Shi, Pengcheng Ma, Ting Du, Yuxin Bai, Fan Huang, Tiejun Zhao, Bo Wang, Haonan Li, Xiaomeng Gu, Hanxue Dong, Haoyu Yang, Jichen Mazurowski, Maciej A. Gupta, Saumya Wu, Linshan Zhuang, Jiaxin Chen, Hao Roth, Holger Xu, Daguang Blaschko, Matthew B. Decherchi, Sergio Cavalli, Andrea Yuille, Alan L. Zhou, Zongwei Department of Computer Science Johns Hopkins University United States Department of Pharmacy and Biotechnology University of Bologna Italy Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Italy NVIDIA United States Germany Germany ESAT-PSI KU Leuven Belgium Faculty of Mathematics and Computer Science Heidelberg University Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Germany Shanghai Jiao Tong University China Shanghai Artificial Intelligence Laboratory China Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Germany DKFZ Germany School of Computer Science and Engineering Northwestern Polytechnical University China Australian Institute for Machine Learning The University of Adelaide Australia College of Computer Science and Technology Zhejiang University China Hong Kong University of Science and Technology Guangzhou China Hong Kong University of Science and Technology Hong Kong Faculty of Informatics and Data Science University of Regensburg Germany Faculty of Electrical Engineering and Information Technology RWTH Aachen University Germany Fraunhofer Institute for Digital Medicine MEVIS Germany Electronic & Information Engineering School Harbin Institute of Technology Shenzhen China China The Chinese University of Hong Kong Hong Kong Peking University China Department of Electrical and Computer Engineering Duke University United States Stony Brook University United States Department of Computer Science and Engineering Department of Chemical and Biological Engineering Division of Life Science Hong Kong University of Science and Technology Hong Kong Data Science and Computation Facility Fondazione Istituto Italiano di Tecnologia Italy Ecole Polytechnique Fédérale de Lausanne Switzerland
How can we test AI performance? This question seems trivial, but it isn’t. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified metrics, unfair comparisons, and sho... 详细信息
来源: 评论
Advanced Process Control in Manufacturing Using IoT Devices and Artificial Neural Networks
Advanced Process Control in Manufacturing Using IoT Devices ...
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Sustainable Expert Systems (ICSES), International Conference on
作者: V. Sumathi Ramesh S Chethan Chandra S Basavaraddi Visumathi J Ishwarya M.V S. Srinivasan Department of Mathematics Sri Sairam Engineering College Chennai Tamil Nadu India Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India Department of Artificial Intelligence and Machine Learning R&D Don Bosco Institute of Technology VTU Belagavi Karnataka India Department of Information Technology Veltech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Artificial intelligence and Data science Department Agni College of Technology Chennai Tamil Nadu India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India
Optimization of industrial activities is significantly helped by Advanced Process Control (APC), which increases efficiency, decreases costs, and improves product quality. Artificial Neural Networks (ANNs) and the Int... 详细信息
来源: 评论
Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials
arXiv
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arXiv 2023年
作者: Lee, Siwoo Heinen, Stefan Khan, Danish Von Lilienfeld, O. Anatole Department of Chemistry University of Toronto St. George campus TorontoON Canada Vector Institute for Artificial Intelligence TorontoONM5S 1M1 Canada Acceleration Consortium University of Toronto 80 St George St TorontoONM5S 3H6 Canada Department of Materials Science and Engineering University of Toronto St. George campus TorontoON Canada Department of Physics University of Toronto St. George campus TorontoON Canada Machine Learning Group Technische Universität Berlin Berlin Institute for the Foundations of Learning and Data Berlin Germany
We present an automated data-collection pipeline involving a convolutional neural network and a large language model to extract user-specified tabular data from peer-reviewed literature. The pipeline is applied to 74 ... 详细信息
来源: 评论
Improved decision making with similarity based machine learning: Applications in chemistry
arXiv
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arXiv 2022年
作者: Lemm, Dominik von Rudorff, Guido Falk von Lilienfeld, O. Anatole University of Vienna Faculty of Physics Kolingasse 14-16 ViennaAT-1090 Austria University of Vienna Vienna Doctoral School in Physics Boltzmanngasse 5 ViennaAT-1090 Austria Departments of Chemistry Materials Science and Engineering and Physics University of Toronto St. George Campus TorontoON Canada Vector Institute for Artificial Intelligence TorontoONM5S 1M1 Canada Machine Learning Group Technische Universität Berlin Institute for the Foundations of Learning and Data Berlin10587 Germany
Despite the fundamental progress in autonomous molecular and materials discovery, data scarcity throughout chemical compound space still severely hampers the use of modern ready-made machine learning models as they re... 详细信息
来源: 评论