Computational assessment identifies probe binding errors in a widely used commercial platform for spatial transcriptomics.
Abstract: Accurate liver and tumor segmentation in CT images is vital for diagnosis and treatment planning. This study presents SegResNet_2335, a lightweight 3D residual network optimized for ...
Exploring the Past and Current Landscape of Biomarker-Driven Clinical Trials Through Large Language Models First, we pretrained the encoder of a transformer-based network using a self-supervised ...
Early identification of the primary tumor types in brain metastases (BMs) is crucial for developing effective treatment strategies. This study aimed to evaluate the potential of multiparametric MRI ...
WESTWEGO, La. — Robin Phillip’s fresh haircut is dyed her favorite color — green. But beneath the dye job is a scar that runs along the side of her head, the result of two craniotomies. Subscribe to ...
ABSTRACT: Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving ...
ABSTRACT: Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving ...
As cancer cases have increased worldwide, the disease has become more complex, presenting challenges to scientific advances in diagnosis and treatment. In this context, artificial intelligence (AI) ...
Abstract: The most severe cancer that causes death is brain tumor (BT). Even after standard treatment, few of the huge grade BT easily recurrent. While managing patient results, a critical component ...
Other AI tools have been developed for cancer screenings, however, those tools used static images. iSeg uses 3D imagery for a deeper understanding of the tumor, including how it moves as a patient ...
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