PURPOSE: This study aimed to develop a deep learning (DL) model for brain region parcellation using CT data from PET/CT scans to enable accurate amyloid quantification in 18 F-FBB PET/CT without relying on high-resolution MRI.
AIM: Prospective outcome prediction plays a crucial role in guiding preoperative decision-making in patients with Chiari malformation type I (CM-Ⅰ) with syringomyelia. Here, we aimed to develop a predictive model for postoperative outcomes in patient...
AIM: To develop and validate a machine learning (ML) model based on positron emission tomography/computed tomography (PET/CT) multi-modality fusion radiomics to improve the prediction efficiency of mediastinal-hilar lymph node metastasis (LNM).
International journal of medical informatics
Jan 29, 2025
PURPOSE: Neuroblastoma (NB) is a childhood malignancy with a poor prognosis and a propensity for distant metastasis (DM). We aimed to establish machine learning (ML) based model to accurately predict risk of DM and prognosis of NB patients with DM.
International journal of medical informatics
Jan 29, 2025
PURPOSE: To develop and validate a novel artificial intelligence model for predicting the initial empiric dose of vancomycin, with the aim of achieving an area under the concentration-time curve (AUC) of 400-600 mg∙h/L, using individual clinical data...
Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technique pivotal for understanding human neural mechanisms of intricate cognitive processes. Most rs-fMRI studies compute a single static functional connectivity matrix a...
PURPOSE: This study aims to assess whether the novel CovBat harmonization method can further reduce radiomics feature variability from different imaging devices in multi-center studies and improve machine learning model performance compared to the Co...
OBJECTIVES: To convert 1D spectra into 2D images using the Gramian angular field, to be used as input for convolutional neural network for classification tasks such as glioblastoma versus lymphoma.
The international journal of cardiovascular imaging
Jan 29, 2025
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MP...
The diagnostic landscape of brain tumors integrates comprehensive molecular markers alongside traditional histopathological evaluation. DNA methylation and next-generation sequencing (NGS) have become a cornerstone in central nervous system (CNS) tum...
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