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Ergebnis der Suche nach: "Machine Learning"
im Bestand: Gesamter Bestand

16941 - 16950 von 17051
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Artikel 16941 Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain
Enthalten in Scientific reports Bd. 14, 12.8.2024, Nr. 1, date:12.2024: 1-24
Online Ressource
Artikel 16942 Utilizing machine learning to facilitate the early diagnosis of posterior circulation stroke
Enthalten in BMC neurology Bd. 24, 7.5.2024, Nr. 1, date:12.2024: 1-12
Online Ressource
Artikel 16943 Utilizing machine learning to identify fall predictors in India's aging population: findings from the LASI
Enthalten in BMC geriatrics Bd. 25, 17.3.2025, Nr. 1, date:12.2025: 1-11
Online Ressource
Artikel 16944 Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine)
Enthalten in Scientific reports Bd. 15, 24.1.2025, Nr. 1, date:12.2025: 1-13
Online Ressource
Artikel 16945 Utilizing machine learning to predict participant response to follow-up health surveys in the Millennium Cohort Study
Enthalten in Scientific reports Bd. 14, 28.10.2024, Nr. 1, date:12.2024: 1-12
Online Ressource
Artikel 16946 Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction
Enthalten in Scientific reports Bd. 14, 23.5.2024, Nr. 1, date:12.2024: 1-13
Online Ressource
Artikel 16947 Utilizing Ni(II) complex for metal drug-gel particles in cervical cancer treatment and designing novel drugs through machine learning methods
Enthalten in Scientific reports Bd. 14, 5.3.2024, Nr. 1, date:12.2024: 1-9
Online Ressource
Artikel 16948 Utilizing reinforcement learning for de novo drug design
Enthalten in Machine learning Bd. 113, 8.4.2024, Nr. 7, date:7.2024: 4811-4843
Online Ressource
Artikel 16949 Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand
Enthalten in Scientific reports Bd. 15, 11.3.2025, Nr. 1, date:12.2025: 1-12
Online Ressource
Artikel 16950 Validating administrative data to identify complex surgical site infections following cardiac implantable electronic device implantation: a comparison of traditional methods and machine learning
Enthalten in Antimicrobial resistance and infection control Bd. 11, 10.11.2022, Nr. 1, date:12.2022: 1-9
Online Ressource


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