Leveraging Artificial Intelligence for Improved Cancer Imaging and Patient Outcomes
DOI:
https://doi.org/10.48047/yhhcfs50Keywords:
Artificial intelligence, cancer imaging, machine learning, deep learning, predictive modeling, personalized medicine.Abstract
Although cancer ranks as one of the major causes of death globally, there is an ever increasing need for development in diagnostic
and treatment methods. Existing cancer detection and monitoring, depending on traditional imaging means such as magnetic
resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), rely to a great extent on
images that may vary from person to person. Unfortunately, these techniques have problems with accuracy, with efficiency, and
accessibility. Among the latest tools that have been proven as transforming in cancer imaging are artificial intelligence, especially
machine learning (ML), and more recently deep learning (DL), that have shown advantages in tumor detection, segmentation
and cancer predictive modeling.
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References
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