Artificial Intelligence and Machine Learning in Cancer Prognosis, Prediction, and Treatment Selection- A Critical Perspective

Cancer is the major cause of morbidity and mortality globally. While there has been improvement in cancer diagnosis, prognosis, and therapy, providing tailored and data-driven care remains a problem. Artificial intelligence (AI), which is used to forecast and automate numerous malignancies, has emerged as a promising solution for increasing healthcare accuracy and patient outcomes. AI applications in oncology include risk assessment, early diagnosis, patient prognosis prediction, and treatment selection based on extensive information. Machine learning (ML), a form of artificial intelligence that allows computers to learn from training data, has proven to be highly effective in predicting cancers such as breast, brain, lung, liver, and prostate. AI and machine learning have outperformed physicians at predicting cancer. Not only could these technologies enhance cancer detection and prognosis, but they may also improve patients' quality of life overall. Therefore, it is important to improve current AI and ML technologies and to develop new programs to benefit patients. This article examines the use of AI and ML algorithms in cancer prediction, including their current applications, limitations, and prospects.