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35671 |
Understanding Colour Tuning Rules and Predicting Absorption Wavelengths of Microbial Rhodopsins by Data-Driven Machine-Learning Approach
Enthalten in Scientific reports Bd. 8, 22.10.2018, Nr. 1, date:12.2018: 1-11
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35672 |
Understanding current states of machine learning approaches in medical informatics: a systematic literature review
Enthalten in Health and Technology Bd. 11, 14.3.2021, Nr. 3, date:5.2021: 471-482
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35673 |
Understanding EMS response times: a machine learning-based analysis
Enthalten in BMC medical informatics and decision making Bd. 25, 24.3.2025, Nr. 1, date:12.2025: 1-15
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35674 |
Understanding health management and safety decisions using signal processing and machine learning
Enthalten in BMC medical research methodology Bd. 19, 13.6.2019, Nr. 1, date:12.2019: 1-12
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35675 |
Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models
Enthalten in Neuroinformatics Bd. 22, 10.9.2024, Nr. 4, date:10.2024: 487-497
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35676 |
Understanding live oil composition effect on asphaltene precipitation as a function of temperature change during depressurization using machine learning techniques
Enthalten in Chemical papers Bd. 79, 16.11.2024, Nr. 1, date:1.2025: 353-364
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35677 |
Understanding machine learning applications in dementia research and clinical practice: a review for biomedical scientists and clinicians
Enthalten in Alzheimer's research & therapy Bd. 16, 1.8.2024, Nr. 1, date:12.2024: 1-21
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35678 |
Understanding machine learning software defect predictions
Enthalten in Automated software engineering Bd. 27, 12.10.2020, Nr. 3-4, date:12.2020: 369-392
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35679 |
Understanding of Wetting Mechanism Toward the Sticky Powder and Machine Learning in Predicting Granule Size Distribution Under High Shear Wet Granulation
Enthalten in American Association of Pharmaceutical Scientists: AAPS PharmSciTech Bd. 25, 23.10.2024, Nr. 8, date:12.2024: 1-22
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35680 |
Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations
Enthalten in npj computational materials Bd. 11, 2.3.2025, Nr. 1, date:12.2025: 1-9
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