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11581 |
Survival machine learning model of T1 colorectal postoperative recurrence after endoscopic resection and surgical operation: a retrospective cohort study
Enthalten in BMC cancer Bd. 25, 14.2.2025, Nr. 1, date:12.2025: 1-11
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11582 |
Survival prediction in diffuse large B-cell lymphoma patients: multimodal PET/CT deep features radiomic model utilizing automated machine learning
Enthalten in Journal of cancer research and clinical oncology Bd. 150, 9.10.2024, Nr. 10, date:10.2024: 1-13
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11583 |
Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques
Enthalten in BMC medical research methodology Bd. 20, 16.11.2020, Nr. 1, date:12.2020: 1-14
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11584 |
Survival prediction of glioblastoma patients using machine learning and deep learning: a systematic review
Enthalten in BMC cancer Bd. 24, 27.12.2024, Nr. 1, date:12.2024: 1-36
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11585 |
Survival prediction of glioblastoma patients using modern deep learning and machine learning techniques
Enthalten in Scientific reports Bd. 14, 29.1.2024, Nr. 1, date:12.2024: 1-12
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11586 |
Survival trend and outcome prediction for pediatric Hodgkin and non-Hodgkin lymphomas based on machine learning
Enthalten in Clinical and experimental medicine Bd. 24, 18.6.2024, Nr. 1, date:12.2024: 1-11
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11587 |
Sustainable EnergySense: a predictive machine learning framework for optimizing residential electricity consumption
Enthalten in Discover sustainability Bd. 5, 4.4.2024, Nr. 1, date:12.2024: 1-11
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11588 |
Sustainable power management in light electric vehicles with hybrid energy storage and machine learning control
Enthalten in Scientific reports Bd. 14, 7.3.2024, Nr. 1, date:12.2024: 1-21
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11589 |
SVFX: a machine learning framework to quantify the pathogenicity of structural variants
Enthalten in Genome biology Bd. 21, 9.11.2020, Nr. 1, date:12.2020: 1-21
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|
11590 |
SVLearn: a dual-reference machine learning approach enables accurate cross-species genotyping of structural variants
Enthalten in Nature Communications Bd. 16, 11.3.2025, Nr. 1, date:12.2025: 1-14
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