Cancers, Free Full-Text
Por um escritor misterioso
Descrição
The use of multiparametric magnetic resonance imaging (mpMRI) has become a common technique used in guiding biopsy and developing treatment plans for prostate lesions. While this technique is effective, non-invasive methods such as radiomics have gained popularity for extracting imaging features to develop predictive models for clinical tasks. The aim is to minimize invasive processes for improved management of prostate cancer (PCa). This study reviews recent research progress in MRI-based radiomics for PCa, including the radiomics pipeline and potential factors affecting personalized diagnosis. The integration of artificial intelligence (AI) with medical imaging is also discussed, in line with the development trend of radiogenomics and multi-omics. The survey highlights the need for more data from multiple institutions to avoid bias and generalize the predictive model. The AI-based radiomics model is considered a promising clinical tool with good prospects for application.
Cancers, Free Full-Text
Cancers, Free Full-Text
.jpg)
Thoracic Cancer - Wiley Online Library
ROS in cancer therapy: the bright side of the moon
Cancers, Free Full-Text
from Flow Cytometry to Cytomics, Page 2
Cancers, Free Full-Text
Spatial genomics maps the structure, nature and evolution of cancer clones
Celltracker Zip Get File - Colaboratory
Sotorasib for Lung Cancers with KRAS p.G12C Mutation
PDF) Combination of tumor markers predicts progression and pathological response in patients with locally advanced gastric cancer after neoadjuvant chemotherapy treatment
Weekly Paclitaxel in the Adjuvant Treatment of Breast Cancer
