Review on Artificial Intelligence in Cancer Research; diagnosis, prognosis and prediction

Background: Cancer remains a significant global health issue and is currently the second leadingcause of death in the United States. Early diagnosis and early cancer detection increasesthe chances of receiving effective treatment for many tumor groups. Utilizing artificial intelligence(AI) specially Machine learning(ML), where computers learn complex data patterns tomake predictions, sheds new light in the field of cancer research specifically in the context ofprediction, diagnosis and prognosis.Method: PubMed and Medline were screened for articles developing AI in the settings of diagnosis,prognosis or prediction from ۲۰۲۰ onwards.Results: ML as one the most important domains of AI, has been emerged as a promising tool incancer diagnosis, leveraging complex patterns in medical imaging, laboratory results, and patientrecords to predict cancer development and progression. Multidisciplinary collaborations are essentialto overcome the challenges of implementing AI and ML in cancer diagnosis. Radiomicsand radio genomics analyses are being explored to discover objective mathematical features forintegrated diagnostics in disease management. The successful application of AI for diagnosticpurposes in cancer imaging has led to the exploration of AI-based imaging analysis for addressingcomplex clinical needs. AI-based predictive models have demonstrated their value in treatmentselection and identifying patients who would benefit most from intensive therapies. This approachhas resulted in improved patient outcomes and survival rates, while also minimizing unnecessaryharm from aggressive treatments for low-risk patients. In the field of radiology, AI has beenutilized to identify novel predictive and prognostic biomarkers, enabling more informed clinicaldecision-making.Conclusion: Collectively, the use of AI and machine learning in cancer research has shown greatpromise in improving the accuracy and efficiency of cancer diagnosis, prognosis, and treatmentselection. With continued research and development, the integration of these technologies intoclinical practice has the potential to revolutionize cancer management and improve patient outcomes.

کلیدواژه ها:

artificial intelligence ، cancer ، predict ، prognosis ، diagnosis