AIMC Topic: Retrospective Studies
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Predicting branch retinal vein occlusion development using multimodal deep learning and pre-onset fundus hemisection images.
Scientific reports
Jan 21, 2025
Branch retinal vein occlusion (BRVO) is a leading cause of visual impairment in working-age individuals, though predicting its occurrence from retinal vascular features alone remains challenging. We developed a deep learning model to predict BRVO bas...
Predicting postoperative adhesive small bowel obstruction in infants under 3 months with intestinal malrotation: a random forest approach.
Jornal de pediatria
Jan 21, 2025
OBJECTIVE: This study aimed to develop a predictive model using a random forest algorithm to determine the likelihood of postoperative adhesive small bowel obstruction (ASBO) in infants under 3 months with intestinal malrotation.
A Machine Learning Model for Predicting the HER2 Positive Expression of Breast Cancer Based on Clinicopathological and Imaging Features.
Academic radiology
Jan 20, 2025
RATIONALE AND OBJECTIVES: To develop a machine learning (ML) model based on clinicopathological and imaging features to predict the Human Epidermal Growth Factor Receptor 2 (HER2) positive expression (HER2-p) of breast cancer (BC), and to compare its...
Diagnostic accuracy of an automated classifier for the detection of pleural effusions in patients undergoing lung ultrasound.
The American journal of emergency medicine
Jan 20, 2025
RATIONALE: Lung ultrasound, the most precise diagnostic tool for pleural effusions, is underutilized due to healthcare providers' limited proficiency. To address this, deep learning models can be trained to recognize pleural effusions. However, curre...
Deep learning-based MVIT-MLKA model for accurate classification of pancreatic lesions: a multicenter retrospective cohort study.
La Radiologia medica
Jan 20, 2025
BACKGROUND: Accurate differentiation between benign and malignant pancreatic lesions is critical for effective patient management. This study aimed to develop and validate a novel deep learning network using baseline computed tomography (CT) images t...
Research on predicting radiographic exposure time in imaging based on neural network prediction models.
Clinical neurology and neurosurgery
Jan 20, 2025
OBJECTIVE: To explore the anatomical and clinical factors that affect the radiographic exposure time in radial artery cerebral angiography and to establish a model.
Interpretable Machine Learning Model for Predicting Postpartum Depression: Retrospective Study.
JMIR medical informatics
Jan 20, 2025
BACKGROUND: Postpartum depression (PPD) is a prevalent mental health issue with significant impacts on mothers and families. Exploring reliable predictors is crucial for the early and accurate prediction of PPD, which remains challenging.
Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors.
BMC medical imaging
Jan 18, 2025
OBJECTIVES: The objective is to develop and validate intratumoral and peritumoral ultrasomics models utilizing endoscopic ultrasonography (EUS) to predict pathological grading in pancreatic neuroendocrine tumors (PNETs).
The efficiency of artificial intelligence for management and clinical decision-making in the identification of patients with hidden HCV infection (Intelligen-C strategy).
Gastroenterologia y hepatologia
Jan 18, 2025
INTRODUCTION: Artificial intelligence (AI) allows the optimization of diagnostic processes for hepatitis C virus (HCV) patients. Our objective was to evaluate the clinical, economic, and management benefits of an AI-based clinical decision support sy...
TagGen: Diffusion-based generative model for cardiac MR tagging super resolution.
Magnetic resonance in medicine
Jan 17, 2025
PURPOSE: The aim of the work is to develop a cascaded diffusion-based super-resolution model for low-resolution (LR) MR tagging acquisitions, which is integrated with parallel imaging to achieve highly accelerated MR tagging while enhancing the tag g...
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