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26711 |
The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches
Enthalten in Arthritis Research & Therapy Bd. 21, 9.11.2019, Nr. 1, date:12.2019: 1-10
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26712 |
The features associated with mammography-occult MRI-detected newly diagnosed breast cancer analysed by comparing machine learning models with a logistic regression model
Enthalten in La Radiologia medica Bd. 129, 21.3.2024, Nr. 5, date:5.2024: 751-766
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26713 |
The Firm Life Cycle Forecasting Model Using Machine Learning Based on News Articles
Enthalten in International journal of networked and distributed computing Bd. 9, 5.1.2021, Nr. 1, date:1.2021: 1-9
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26714 |
The framing of time-dependent machine learning models improves risk estimation among young individuals with acute coronary syndromes
Enthalten in Scientific reports Bd. 13, 19.1.2023, Nr. 1, date:12.2023: 1-14
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26715 |
The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium
Enthalten in Molecular psychiatry Bd. 28, 2.5.2023, Nr. 10, date:10.2023: 4307-4319
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26716 |
The future of machine learning for small-molecule drug discovery will be driven by data
Enthalten in Nature computational science Bd. 4, 15.10.2024, Nr. 10, date:10.2024: 735-743
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26717 |
The Game of Drones: rapid agent-based machine-learning models for multi-UAV path planning
Enthalten in Computational mechanics Bd. 65, 16.9.2019, Nr. 1, date:1.2020: 217-228
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26718 |
The Goldilocks paradigm: comparing classical machine learning, large language models, and few-shot learning for drug discovery applications
Enthalten in Communications chemistry Bd. 7, 12.6.2024, Nr. 1, date:12.2024: 1-11
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26719 |
The greedy side of the LASSO: new algorithms for weighted sparse recovery via loss function-based orthogonal matching pursuit
Enthalten in Sampling theory, signal processing, and data analysis Bd. 23, 10.2.2025, Nr. 1, date:6.2025: 1-40
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26720 |
The growth–environment nexus amid geopolitical risks: cointegration and machine learning algorithm approaches
Enthalten in Discover sustainability Bd. 6, 7.2.2025, Nr. 1, date:12.2025: 1-24
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