PREDICT SURVIVAL PROBABILITY FOR CANCER PATIENTSUSING DEEP LEARNING

PREDICT SURVIVAL PROBABILITY FOR CANCER PATIENTS USING DEEP LEARNING

Anupam Gupta, Kunal Aggarwal, Rishabh Kumar, Kavita Saxena, Deepti Gupta

Abstract - Deep learning is a type of machine learning that uses artificial neural networks to learn and make decisions based on data. It has been applied in various fields, including healthcare, to predict the survival probability of cancer patients.One way deep learning has been used in this context is by analyzing medical images, such as CT

scans or MRI scans, to identify patterns and features that may be indicative of a patient's prognosis. For example, a deep learning model might be trained on a large dataset of medical images and patient outcomes to identify certain features in the images that are associated with a higher or lower probability of survival.

Another approach is to use deep learning to analyze other types of data, such as patient demographics, medical history, and treatment information, to predict survival probabilities. This may involve using a combination of different types of data and features, such as age, gender, and stage of cancer, in addition to medical images.Overall, the use of deep learning in predicting the survival probability of cancer patients has the potential to improve the accuracy and speed of diagnosis and treatment planning. However, it is important to note that these predictions are not always 100% accurate and should be considered in conjunction with other clinical information and expert judgment.

Keywords- DICOM, CNN, Convolutional Neural Networks, DLS, Deep Learning System, Pre-processing, Features Extraction, Adam Optimizer