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A magnetic resonance imaging (MRI)-based deep learning radiomics model predicts recurrence-free survival in lung cancer patients after surgical resection of brain metastases.
Clinical radiology
Apr 2, 2025
AIM: To develop and validate a magnetic resonance imaging (MRI)-based deep learning radiomics model (DLRM) to predict recurrence-free survival (RFS) in lung cancer patients after surgical resection of brain metastases (BrMs).
Coronary artery disease severity and location detection using deep-mining-based magnetocardiography pattern features.
Computer methods and programs in biomedicine
Apr 2, 2025
BACKGROUND AND OBJECTIVE: The objective of this study was to develop an automated, accurate method of assessing coronary artery disease (CAD), including its severity and location, using deep-mining-based magnetocardiography (MCG) pattern features.
Personalized glucose forecasting for people with type 1 diabetes using large language models.
Computer methods and programs in biomedicine
Apr 2, 2025
BACKGROUND AND OBJECTIVE: Type 1 Diabetes (T1D) is an autoimmune disease that requires exogenous insulin via Multiple Daily Injections (MDIs) or subcutaneous pumps to maintain targeted glucose levels. Despite the advances in Continuous Glucose Monito...
Data independent acquisition proteomics and machine learning reveals that proteins associated with immunity are potential molecular markers for early diagnosis of autism.
Clinica chimica acta; international journal of clinical chemistry
Apr 2, 2025
BACKGROUND: Early diagnosis of autism is critical to its treatment, but so far, there is no clear molecular marker for early diagnosis in children.
Machine learning models based on a national-scale cohort accurately identify patients at high risk of deep vein thrombosis following primary total hip arthroplasty.
Orthopaedics & traumatology, surgery & research : OTSR
Apr 2, 2025
BACKGROUND: The occurrence of deep venous thrombosis (DVT) following total hip arthroplasty (THA) poses a substantial risk of morbidity and mortality, highlighting the need for preoperative risk stratification and prophylaxis initiatives. However, th...
Generating Synthetic T2*-Weighted Gradient Echo Images of the Knee with an Open-source Deep Learning Model.
Academic radiology
Apr 2, 2025
RATIONALE AND OBJECTIVES: Routine knee MRI protocols for 1.5 T and 3 T scanners, do not include T2*-w gradient echo (T2*W) images, which are useful in several clinical scenarios such as the assessment of cartilage, synovial blooming (deposition of he...
Neural networks can accurately identify individual runners from their foot kinematics, but fail to predict their running performance.
Journal of biomechanics
Apr 2, 2025
Athletes and coaches may seek to improve running performance through adjustments to running form. Running form refers to the biomechanical characteristics of a runner's movement, and can distinguish individual runners as well as groups of runners, su...
Automated segmentation of the dorsal root ganglia in MRI.
NeuroImage
Apr 2, 2025
The dorsal root ganglion (DRG) contains all primary sensory neurons, but its functional role in somatosensory and pain processing remains unclear. Recently, MR imaging techniques have been developed for objective in vivo observation of the DRG. In pa...
Curriculum is more influential than haptic feedback when learning object manipulation.
Science advances
Apr 2, 2025
Dexterous manipulation remains an aspirational goal for autonomous robotic systems, particularly when learning to lift and rotate objects against gravity with intermittent finger contacts. We use model-free reinforcement learning to compare the effec...
Machine Learning Models for Frailty Classification of Older Adults in Northern Thailand: Model Development and Validation Study.
JMIR aging
Apr 2, 2025
BACKGROUND: Frailty is defined as a clinical state of increased vulnerability due to the age-associated decline of an individual's physical function resulting in increased morbidity and mortality when exposed to acute stressors. Early identification ...
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