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26591 |
The biomedical knowledge graph of symptom phenotype in coronary artery plaque: machine learning-based analysis of real-world clinical data
Enthalten in BioData Mining Bd. 17, 21.5.2024, Nr. 1, date:12.2024: 1-17
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26592 |
The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition
Enthalten in BMC cardiovascular disorders Bd. 21, 13.10.2021, Nr. 1, date:12.2021: 1-8
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26593 |
The BSM-AI project: SUSY-AI–generalizing LHC limits on supersymmetry with machine learning
Enthalten in The European physical journal / C / Particles and fields Bd. 77, 24.4.2017, Nr. 4, date:4.2017: 1-25
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26594 |
The classification of leek seeds based on fluorescence spectroscopic data using machine learning
Enthalten in European food research and technology Bd. 249, 12.9.2023, Nr. 12, date:12.2023: 3217-3226
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26595 |
The classification of medical and botanical data through majority voting using artificial neural network
Enthalten in International journal of information technology Bd. 15, 11.7.2023, Nr. 6, date:8.2023: 3271-3283
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26596 |
The combination of machine learning and untargeted metabolomics identifies the lipid metabolism -related gene CH25H as a potential biomarker in asthma
Enthalten in Inflammation research Bd. 72, 20.4.2023, Nr. 5, date:5.2023: 1099-1119
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26597 |
The company we keep. Using hemodialysis social network data to classify patients’ kidney transplant attitudes with machine learning algorithms
Enthalten in BMC nephrology Bd. 23, 29.12.2022, Nr. 1, date:12.2022: 1-12
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26598 |
The Construction and Migration of a Multi-source Integrated Drought Index Based on Different Machine Learning
Enthalten in Water resources management Bd. 37, 9.10.2023, Nr. 15, date:12.2023: 5989-6004
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26599 |
The construction of machine learning-based predictive models for high-quality embryo formation in poor ovarian response patients with progestin-primed ovarian stimulation
Enthalten in Reproductive biology and endocrinology Bd. 22, 10.7.2024, Nr. 1, date:12.2024: 1-11
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26600 |
The CT-based intratumoral and peritumoral machine learning radiomics analysis in predicting lymph node metastasis in rectal carcinoma
Enthalten in BMC gastroenterology Bd. 22, 16.11.2022, Nr. 1, date:12.2022: 1-8
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