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11301 |
Quantifying wood decomposition by insects and fungi using computed tomography scanning and machine learning Enthalten in Scientific reports Bd. 12, 27.9.2022, Nr. 1, date:12.2022: 1-12
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11302 |
QuantImage v2: a comprehensive and integrated physician-centered cloud platform for radiomics and machine learning research Enthalten in European radiology experimental Bd. 7, 22.3.2023, Nr. 1, date:12.2023: 1-13
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11303 |
Quantitative classification evaluation model for tight sandstone reservoirs based on machine learning Enthalten in Scientific reports Bd. 14, 5.9.2024, Nr. 1, date:12.2024: 1-20
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11304 |
Quantitative design rules for protein-resistant surface coatings using machine learning Enthalten in Scientific reports Bd. 9, 22.1.2019, Nr. 1, date:12.2019: 1-12
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11305 |
Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies Enthalten in Scientific reports Bd. 12, 11.6.2022, Nr. 1, date:12.2022: 1-10
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11306 |
Quantitative prediction of disinfectant tolerance in Listeria monocytogenes using whole genome sequencing and machine learning Enthalten in Scientific reports Bd. 15, 26.3.2025, Nr. 1, date:12.2025: 1-11
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11307 |
Quantitative texture analysis using machine learning for predicting interpretable pulmonary perfusion from non-contrast computed tomography in pulmonary embolism patients Enthalten in Respiratory research Bd. 25, 28.10.2024, Nr. 1, date:12.2024: 1-15
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11308 |
Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography Enthalten in Nature Communications Bd. 14, 16.11.2023, Nr. 1, date:12.2023: 1-11
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11309 |
Quantum-accurate machine learning potentials for metal-organic frameworks using temperature driven active learning Enthalten in npj computational materials Bd. 10, 8.10.2024, Nr. 1, date:12.2024: 1-13
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11310 |
Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning Enthalten in Quantum machine intelligence Bd. 5, 2.5.2023, Nr. 1, date:6.2023: 1-11
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