Inferential Survey on oncology information systems using predictive analytics

Abstract

Abstract Cancer is one of the deadliest diseases diagnosed among the population across the globe. The number of cases is increasing each year so are the different diagnosis tools and techniques and technologies. Significant increase in the mortality rate worldwide leads to tremendous scope to device and implement latest computer aided diagnostic systems for early detection. One such technique is machine learning coupled with medical imaging modalities that have proved to be efficient in diagnosing various medical conditions. Current study presents a review of different machine learning techniques applied on emerging modalities for cancer diagnosis from 2018 to 2022. It was found that traditional machine learning algorithms like SVM, GMM performed very well in classification. But overall deep learning has dominated the field of medical image analysis. Researchers have achieved 100% accuracy in classification of cancerous and normal tissue images using medical image analysis with the help of machine learning. This survey presents the studies based on Lymphoma cancer analysis based on HIS systems