Abstract
The field of cancer research has been profoundly impacted by the utilization of artificial intelligence (AI), particularly through the analysis of medical records encompassing genomics, transcriptomics, proteomics, and imaging data. Subdomains of AI, such as machine learning (ML) and deep learning (DL), possess the capability to analyze intricate patterns within these records. This allows for groundbreaking advancements in cancer diagnosis, prognosis, and treatment by extracting valuable insights from sources such as histology and radiology imaging. The integration of Al-based models has led to improved prediction, diagnosis, and even treatment of various types of cancer, resulting in enhanced performance within the field of oncology. However, AI also faces challenges including ethical and legal considerations, data quality and accessibility, and issues pertaining to model interpretability. It is crucial to develop and evaluate Al-based systems in collaboration with clinicians and researchers to ensure their safety, reliability, and validity in cancer research.
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CITATION STYLE
Delshad, M., Omrani, M. A., Pourbagheri-Sigaroodi, A., & Bashash, D. (2023, September 1). Oncology in the modern era: Artificial intelligence is reshaping cancer diagnosis, prognosis and treatment. Iranian Journal of Blood and Cancer. Iranian Pediatric Hematology and Oncology Society. https://doi.org/10.61186/ijbc.15.3.13
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