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Design and Development of a Web‐Based Registry for Outpatient Rehabilitation: A Delphi Multi‐Disciplinary, Expert Consensus Study
Published 2025-01-01“…Coding guidelines were derived from the International Classification of Functioning, Disability, and Health. …”
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Utilizing machine-learning techniques on MRI radiomics to identify primary tumors in brain metastases
Published 2025-01-01“…ObjectiveTo develop a machine learning-based clinical and/or radiomics model for predicting the primary site of brain metastases using multiparametric magnetic resonance imaging (MRI).Materials and methodsA total of 202 patients (87 males, 115 females) with 439 brain metastases were retrospectively included, divided into training sets (brain metastases of lung cancer [BMLC] n = 194, brain metastases of breast cancer [BMBC] n = 108, brain metastases of gastrointestinal tumor [BMGiT] n = 48) and test sets (BMLC n = 50, BMBC n = 27, BMGiT n = 12). A total of 3,404 quantitative image features were obtained through semi-automatic segmentation from MRI images (T1WI, T2WI, FLAIR, and T1-CE). …”
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Dutch Validation of the Self-Evaluation of Negative Symptoms Scale (SNS)
Published 2024-12-01Get full text
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Assessment of Geriatric Problems and Risk Factors for Delirium in Surgical Medicine: Protocol for Multidisciplinary Prospective Clinical Study
Published 2025-01-01“…In addition, a telephone follow-up will be performed 3, 6, and 12 months after discharge. ResultsRecruitment started in August 2022, with 421 patients already recruited at the time of submission. …”
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Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis
Published 2013-01-01Get full text
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Metabolite profiling in assessing ulcerative colitis activity: A systematic review
Published 2025-03-01Get full text
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Emotional regulation as a transdiagnostic category through clinical problems: a narrative study
Published 2021-12-01Get full text
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Development and Validation of a Routine Electronic Health Record-Based Delirium Prediction Model for Surgical Patients Without Dementia: Retrospective Case-Control Study
Published 2025-01-01“…AUROCs were highest for XGB models trained on 12 months of preadmission data. The best-performing XGB model achieved a mean AUROC of 0.79 (SD 0.01) on the holdout set, which decreased to 0.69-0.74 (SD 0.02) when externally validated on data from other hospitals. …”
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Machine learning derivation of two cardiac arrest subphenotypes with distinct responses to treatment
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Severity Assessment of COVID-19 Using a CT-Based Radiomics Model
Published 2021-01-01Get full text
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