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Deep learning to identify stroke within 4.5 h using DWI and FLAIR in a prospective multicenter study.
Scientific reports
Jul 19, 2025
To enhance thrombolysis eligibility in acute ischemic stroke, we developed a deep learning model to estimate stroke onset within 4.5 h using diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) images. Given the variabilit...
Automatic generation and risk stratification of carotid plaque in virtual shear wave elastography using a generative adversarial network.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 18, 2025
Shear wave elastography (SWE) is an effective ultrasound imaging technique for assessing carotid plaque vulnerability. However, acquiring SWE images typically requires costly specialized equipment and must be performed by experienced radiologists, wh...
Visualized load-bearing-based robot control system improves early function in femoral neck fracture patients: a randomized controlled trial focusing on outcomes after total hip arthroplasty.
Journal of orthopaedic surgery and research
Jul 18, 2025
BACKGROUND: After total hip arthroplasty (THA), standing and walking balance are greatly affected in the early recovery period, making it important to increase weight-bearing amount (WBA) on the surgical side. Sometimes, traditional treatment methods...
Collaborative assessment of the risk of postoperative progression in early-stage non-small cell lung cancer: a robust federated learning model.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jul 18, 2025
BACKGROUND: While the TNM staging system provides valuable insights into the extent of disease, predicting postoperative progression in early-stage non-small cell lung cancer (NSCLC) remains a significant challenge. An effective bioimaging prognostic...
AI-Driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes.
Cardiovascular diabetology
Jul 18, 2025
BACKGROUND: Epicardial adipose tissue (EAT) is associated with cardiometabolic risk in type 2 diabetes (T2D), but its spatial distribution and structural alterations remain understudied. We aim to develop a shape-aware, AI-based method for automated ...
Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules.
BMC medical informatics and decision making
Jul 18, 2025
BACKGROUND: Pulmonary Nodules (PNs) are a trend considered as the early manifestation of lung cancer. Among them, PNs that remain stable for more than two years or whose pathological results suggest not being lung cancer are considered benign PNs (BP...
Sex estimation with parameters of the facial canal by computed tomography using machine learning algorithms and artificial neural networks.
BMC medical imaging
Jul 18, 2025
BACKGROUND: The skull is highly durable and plays a significant role in sex determination as one of the most dimorphic bones. The facial canal (FC), a clinically significant canal within the temporal bone, houses the facial nerve. This study aims to ...
Determination of lung cancer exhaled breath biomarkers using machine learning-a new analysis framework.
Scientific reports
Jul 18, 2025
Exhaled breath samples of lung cancer patients (LC), tuberculosis (TB) patients and asymptomatic controls (C) were analyzed using gas chromatography-mass spectrometry (GC-MS). Ten volatile organic compounds (VOCs) were identified as possible biomarke...
Machine learning for the prediction of augmented renal clearance (ARC) in patients with sepsis in critical care units.
Scientific reports
Jul 18, 2025
This study aims to establish and validate prediction models based on novel machine learning (ML) algorithms for augmented renal clearance (ARC) in critically ill patients with sepsis. Patients with sepsis were extracted from the Medical Information M...
Machine learning technology in the classification of glaucoma severity using fundus photographs.
Scientific reports
Jul 18, 2025
This study evaluates the performance of a machine learning model in classifying glaucoma severity using color fundus photographs. Glaucoma severity grading was based on the Hodapp-Parrish-Anderson (HPA) criteria incorporating the mean deviation value...
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