AI and ML-Augmented Analysis For Precision Oncology and Cancer Diagnostics
DOI:
https://doi.org/10.58445/rars.3316Keywords:
Artificial Intelligence (AI), Machine Learning (ML), Cancer diagnosticsAbstract
Each year, nearly 20 million people are diagnosed with a form of cancer, and this number is expected to significantly increase. Despite hundreds of years of research on various cancers, the causes and genetic influences behind them are still not fully understood and current treatment options are, at times, unsuccessful. The recent development of artificial intelligence (AI) and machine learning (ML) tools has the potential to accelerate knowledge of and advancements in cancer screening, diagnostics, and treatment. AI can be incorporated into complex sequencing data sets and clinical imaging to allow for earlier detection of cancer. Similarly, by applying these tools to clinical data, AI and ML can drastically improve diagnostics, allowing for more accuracy in identifying cancer types. Additionally, AI and ML can greatly improve patients’ prognoses by utilizing deep learning to predict patient response to different treatments. In this review, I will discuss the integration of AI and ML technologies into cancer screening, diagnostics, and therapeutic approaches to enhance precision medicine and treatment outcomes for cancer patients.
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