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Predicting mother and newborn skin-to-skin contact using a machine learning approach.
BMC pregnancy and childbirth
Feb 18, 2025
BACKGROUND: Despite the known benefits of skin-to-skin contact (SSC), limited data exists on its implementation, especially its influencing factors. The current study was designed to use machine learning (ML) to identify the predictors of SSC.
Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatch.
Scientific reports
Feb 18, 2025
The presence of a diffusion-weighted imaging (DWI)-fluid-attenuated inversion recovery (FLAIR) mismatch holds potential value in identifying candidates for recanalization treatment. However, the visual assessment of DWI-FLAIR mismatch is subject to l...
The development of an artificial intelligence auto-segmentation tool for 3D volumetric analysis of vestibular schwannomas.
Scientific reports
Feb 18, 2025
Linear and volumetric analysis are the typical methods to measure tumor size. 3D volumetric analysis has risen in popularity; however, this is very time and labor intensive limiting its implementation in clinical practice. This study aims to show tha...
Hybrid Greylag Goose deep learning with layered sparse network for women nutrition recommendation during menstrual cycle.
Scientific reports
Feb 18, 2025
A complex biological process involves physical changes and hormonal fluctuation in the menstrual cycle. The traditional nutrition recommendation models often offer general guidelines but fail to address the specific requirements of women during vario...
Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.
Scientific reports
Feb 18, 2025
This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from African American adults (18-85) in Southeastern Virginia (2016-2020), we found Mood Affective Disorders we...
Integration of 101 machine learning algorithm combinations to unveil m6A/m1A/m5C/m7G-associated prognostic signature in colorectal cancer.
Scientific reports
Feb 18, 2025
Colorectal cancer (CRC) is the most common malignancy in the digestive system, with a lower 5-year overall survival rate. There is increasing evidence showing that RNA modification regulators such as m1A, m5C, m6A, and m7G play crucial roles in tumor...
Developing practical machine learning survival models to identify high-risk patients for in-hospital mortality following traumatic brain injury.
Scientific reports
Feb 18, 2025
Machine learning (ML) offers precise predictions and could improve patient care, potentially replacing traditional scoring systems. A retrospective study at Emtiaz Hospital analyzed 3,180 traumatic brain injury (TBI) patients. Nineteen variables were...
Leveraging OGTT derived metabolic features to detect Binge-eating disorder in individuals with high weight: a "seek out" machine learning approach.
Translational psychiatry
Feb 18, 2025
Binge eating disorder (BED) carries a 6 times higher risk for obesity and accounts for roughly 30% of type 2 diabetes cases. Timely identification of early glycemic disturbances and comprehensive treatment can impact on the likelihood of associated m...
Sub-1-min relaxation-enhanced non-contrast non-triggered cervical MRA using compressed SENSE with deep learning reconstruction in healthy volunteers.
European radiology experimental
Feb 18, 2025
BACKGROUND: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic resonance angiography (MRA) (relaxation-enhanced angiography without contrast and triggering, REACT) of neck arteries using compressed SENSE (CS) com...
Predicting diabetes self-management education engagement: machine learning algorithms and models.
BMJ open diabetes research & care
Feb 18, 2025
INTRODUCTION: Diabetes self-management education (DSME) is endorsed by the American Diabetes Association (ADA) as an essential component of diabetes management. However, the utilization of DSME remains limited in the USA. This study aimed to investig...
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