… cancer is, therefore, vital to its effective and individualized clinical care. The support vector
machine (SVM) is a rising machine … both diagnosis and treatment of most aggressive cancers, …

… In lung cancer, several data points over a patient’s diagnostic … cancer early in diagnosis
and deliver tailored therapy on the basis of available information, both at the time of diagnosis …

… Cancer is a complex and multifaced disorder with thousands of genetic … diagnosis, prognosis,
and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis …

… different types of genomic markers in cancer. This is a discovery type … Machine learning
applications to identify clinical populations at risk for negative outcomes and to aid with diagnosis …

… used in clinical oncology to diagnose cancers, predict patient … and solid tumor biopsies
for cancer diagnosis, prognosis, and … Finally, we examine ML models approved for cancer-related …

… screening programmes such as breast cancer, there are ongoing debates … potential to directly
facilitate cancer diagnosis by triggering … of AI for early cancer diagnosis in symptomatic and …

… We identify mitigation strategies to address ongoing challenges around data availability
and model interpretability in the context of endocrine cancer diagnosis. Finally, we delve into …

… AND artificial intelligence” and “Cancer AND deep learning”, … in connection to early disease
diagnosis, prognosis, and … of our literature overview on cancer diagnosis, prognosis and …

… people received a lung cancer diagnosis. During this training period, the scientists told the
computer which early-stage scans turned out to contain cancerous spots and which did not. …

… of new diagnoses and deaths is 1.9 million and 609 360, respectively. Implementation of
currently existing cancer diagnostic … Cancer diagnosis is rapidly evolving due to continuous …