Personalized cancer treatment; How AI is shaping precision medicine
1 The University of Buckingham, Hunter Street, Buckingham, MK18 1EG, United Kingdom.
2 American University of Anguilla School of Medicine, USA.
3 Public Health and Medical Research, Charisma University, Grace Bay, Turks and Caicos Islands.
Review
World Journal of Biology Pharmacy and Health Sciences, 2024, 19(03), 276–287.
Article DOI: 10.30574/wjbphs.2024.19.3.0622
Publication history:
Received on 01 August 2024; revised on 09 September 2024; accepted on 12 September 2024
Abstract:
The application of artificial intelligence has demonstrated promising outcomes in certain areas of oncology, such as the screening, detection, diagnosis, treatment, and prediction of prognosis for tumors. New learning methods, such as the hybrid learning method, will continue to emerge as artificial intelligence (AI) continues to advance, computer performance continues to improve, and the explosion of various data continues to make it possible for new learning methods to emerge. These new learning methods will further improve the overall performance of the model, including efficient data analysis and accurate prediction. Both machine learning and deep learning have recently produced a model that is capable of analyzing a variety of data sets, which will also boost the prospects of PM. As a conclusion, artificial intelligence-assisted prenatal care has the potential to aid in the early detection, diagnosis, and treatment of cancer. Additionally, it can provide assistance in the selection of the most appropriate treatment plan, so enhancing the prognosis of patients and the outcomes of their treatment.
Keywords:
Artificial Intelligence (AI); Machine Learning (ML); Precision Medicine; Tumor Genomic Profiling; Targeted Therapy
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