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34241 |
Preoperative lower limb kinematic analysis in spinal sagittal imbalance using machine learning and IMU sensors
Enthalten in Signal, image and video processing Bd. 19, 28.5.2025, Nr. 8, date:8.2025: 1-9
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34242 |
Preoperative lymph node metastasis risk assessment in invasive micropapillary carcinoma of the breast: development of a machine learning-based predictive model with a web-based calculator
Enthalten in World journal of surgical oncology Bd. 23, 22.4.2025, Nr. 1, date:12.2025: 1-11
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34243 |
Preoperative multiclass classification of thymic mass lesions based on radiomics and machine learning
Enthalten in Cancer imaging Bd. 25, 6.3.2025, Nr. 1, date:12.2025: 1-11
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34244 |
Preoperative prediction of intrahepatic cholangiocarcinoma lymph node metastasis by means of machine learning: a multicenter study in China
Enthalten in BMC cancer Bd. 22, 29.8.2022, Nr. 1, date:12.2022: 1-11
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34245 |
Preoperative prediction of lymph node status in patients with colorectal cancer. Developing a predictive model using machine learning
Enthalten in International journal of colorectal disease Bd. 37, 26.11.2022, Nr. 12, date:12.2022: 2517-2524
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34246 |
Preoperative prediction of regional lymph node metastasis of colorectal cancer based on 18F-FDG PET/CT and machine learning
Enthalten in Annals of nuclear medicine Bd. 35, 18.3.2021, Nr. 5, date:5.2021: 617-627
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34247 |
Preoperative prediction of the need for arterial and central venous catheterization using machine learning techniques
Enthalten in Scientific reports Bd. 12, 13.7.2022, Nr. 1, date:12.2022: 1-9
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34248 |
Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients
Enthalten in Langenbeck's archives of surgery Bd. 410, 4.1.2025, Nr. 1, date:12.2025: 1-15
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34249 |
Preoperatively predicting failure to achieve the minimum clinically important difference and the substantial clinical benefit in patient-reported outcome measures for total hip arthroplasty patients using machine learning
Enthalten in BMC musculoskeletal disorders Bd. 26, 14.2.2025, Nr. 1, date:12.2025: 1-10
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34250 |
Preovulatory progesterone levels are the top indicator for ovulation prediction based on machine learning model evaluation: a retrospective study
Enthalten in Journal of ovarian research Bd. 17, 21.8.2024, Nr. 1, date:12.2024: 1-11
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