Early Detection of Lung Cancer using Machine Learning Algorithms
DOI:
https://doi.org/10.62760/iteecs.4.2.2025.133Keywords:
Omics datasets, Sequencing technologies, Intricate datasets, Immunotherapy, Machine learningAbstract
Recent advances in imaging and sequencing technology have enabled a systematic advancement in the medical treatment of carcinoma of the lungs. Meanwhile, the human mind's ability to comprehend and make optimal use of the collection for these enormous amounts of knowledge is limited. Through the combination and investigation of this extensive and complex information, lung cancer has been extensively explained using a variety of perspectives from the gathered data, is made possible in great part by machine learning-based methodologies. We give a summary of machine learning based methods in this review that support the various facets of lung cancer treatment as well as diagnosis, involving prognostication, vaccinations, rapid identification, and auxiliary diagnostics. Furthermore, we highlight the challenges and opportunities regarding potential artificial intelligence uses for the illness.
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