Sami Azam

TL;DR: In this article, the authors proposed a model that incorporates different methods to achieve effective prediction of heart disease, which used efficient Data Collection, Data Pre-processing and Data Transformation methods to create accurate information for the training model.

TL;DR: A focused literature survey of Artificial Intelligence (AI) and Machine Learning (ML) methods for intelligent spam email detection, which can help in developing appropriate countermeasures.

TL;DR: The experiment indicates that deep learning algorithms are suitable for intrusion detection in IoT network environment.

TL;DR: In this article, Huang et al. proposed effective image pre-processing methods to create datasets that can save computational time for the neural network and improve accuracy and classification rates for mammographic images.

TL;DR: In this paper, a machine learning-based PV power generation forecasting for both the short and long-term is presented, where different machine learning algorithms, including linear regression, polynomial regression, decision tree regression, support vector regression, random forest regression, long short-term memory, and multilayer perceptron regression, are considered in the study.