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Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up.
NeuroImage
Jan 10, 2025
RATIONALE AND OBJECTIVES: The RANO-BM criteria, which employ a one-dimensional measurement of the largest diameter, are imperfect due to the fact that the lesion volume is neither isotropic nor homogeneous. Furthermore, this approach is inherently ti...
Predicting cognitive decline from neuropsychiatric symptoms and Alzheimer's disease biomarkers: A machine learning approach to a population-based data.
Journal of Alzheimer's disease : JAD
Jan 10, 2025
BACKGROUND: The aim of this study was to examine the potential added value of including neuropsychiatric symptoms (NPS) in machine learning (ML) models, along with demographic features and Alzheimer's disease (AD) biomarkers, to predict decline or no...
Predictive models and determinants of mortality among T2DM patients in a tertiary hospital in Ghana, how do machine learning techniques perform?
BMC endocrine disorders
Jan 10, 2025
BACKGROUND: The increasing prevalence of type 2 diabetes mellitus (T2DM) in lower and middle - income countries call for preventive public health interventions. Studies from Africa including those from Ghana, consistently reveal high T2DM-related mor...
Machine learning in the prediction of human wellbeing.
Scientific reports
Jan 10, 2025
Subjective wellbeing data are increasingly used across the social sciences. Yet, despite the widespread use of such data, the predictive power of approaches commonly used to model wellbeing is only limited. In response, we here use tree-based Machine...
Prediction of mortality risk in patients with severe community-acquired pneumonia in the intensive care unit using machine learning.
Scientific reports
Jan 10, 2025
The aim of this study was to develop and validate a machine learning-based mortality risk prediction model for patients with severe community-acquired pneumonia (SCAP) in the intensive care unit (ICU). We collected data from two centers as the develo...
Deep learning algorithms enable MRI-based scapular morphology analysis with values comparable to CT-based assessments.
Scientific reports
Jan 10, 2025
Scapular morphological attributes show promise as prognostic indicators of retear following rotator cuff repair. Current evaluation techniques using single-slice magnetic-resonance imaging (MRI) are, however, prone to error, while more accurate compu...
Deep learning-based lymph node metastasis status predicts prognosis from muscle-invasive bladder cancer histopathology.
World journal of urology
Jan 10, 2025
PURPOSE: To develop a deep learning (DL) model based on primary tumor tissue to predict the lymph node metastasis (LNM) status of muscle invasive bladder cancer (MIBC), while validating the prognostic value of the predicted aiN score in MIBC patients...
Hypothalamic atrophy in primary lateral sclerosis, assessed by convolutional neural network-based automatic segmentation.
Scientific reports
Jan 10, 2025
Primary lateral sclerosis (PLS) is a motor neuron disease (MND) which mainly affects upper motor neurons. Within the MND spectrum, PLS is much more slowly progressive than amyotrophic laterals sclerosis (ALS). `Classical` ALS is characterized by cata...
Combining machine learning and single-cell sequencing to identify key immune genes in sepsis.
Scientific reports
Jan 10, 2025
This research aimed to identify novel indicators for sepsis by analyzing RNA sequencing data from peripheral blood samples obtained from sepsis patients (n = 23) and healthy controls (n = 10). 5148 differentially expressed genes were identified using...
Developing and validating a machine learning model to predict multidrug-resistant -related septic shock.
Frontiers in immunology
Jan 10, 2025
BACKGROUND: Multidrug-resistant Klebsiella pneumoniae (MDR-KP) infections pose a significant global healthcare challenge, particularly due to the high mortality risk associated with septic shock. This study aimed to develop and validate a machine lea...
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