Decision-Making Approaches for Complex Applications using Deep Learning Models

Decision-making (DM) is the domain that can develop any type of application. Applications such as health care systems, popular product prediction on e-commerce applications, filtering of spam emails, the behavior of the user based on online purchases, etc. Machine learning (ML) algorithms are mainly used to find complex patterns from several domains. Disease prediction is one of the tasks that can work on various diseases to predict accurate diseases according to the given dataset. This task can work efficiently on text data and image data. Many image datasets such as CT scans and MRI images are used to detect the tumors from the brain scan images. Tumors are many types and all the tumors are not cancerous and some tumors are noncancerous. Deep Learning (DL) is the domain that can work better on complex datasets such as decision making. This research is mainly focused on developing the decision-making in several domains such as disease prediction, E-commerce sites, predicting autonomous vehicles (AVs), etc. The performances of several algorithms are also shown in this work.