Masters in Computer Applications, Jawaharlal Nehru Technological University, Hyderabad, Ashok Nagar, India.
Received on 30 March 2024; revised on 05 May 2024; accepted on 07 May 2024
Worldwide, cancer claims more lives than any other disease. Although cancer detection, prognosis, and treatment have all advanced, one major obstacle is the lack of personalized, data-driven care. Artificial intelligence (AI), used to forecast and automate numerous malignancies, has emerged as a viable solution for increasing healthcare accuracy and patient outcomes. Artificial intelligence applications in cancer include risk evaluation, early detection, patient prognosis prediction, and treatment selection based on comprehensive data. Machine learning (ML), a form of artificial intelligence that allows computers to learn from training data, is very successful in predicting breast, brain, lung, liver, and prostate cancers. Indeed, AI and machine learning have outperformed physicians in predicting cancer. These technologies can potentially enhance the diagnosis, prediction, and quality of life of patients with a wide range of disorders, not just cancer. As a result, it is critical to enhance existing AI and ML technologies and create new programs to help patients. This article discusses the use of AI and machine learning algorithms in cancer prediction, including its present uses, future possibilities, and limitations.
Artificial Intelligence; Machine Learning; Cancer Prediction; Early Diagnosis; Deep Learning; Cancer Prevention
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AnandKumar Chennupati. Artificial intelligence and machine learning for early cancer prediction and response. World Journal of Advanced Engineering Technology and Sciences, 2024, 12(01), 035–040. Article DOI: https://doi.org/10.30574/wjaets.2024.12.1.0178