… disease (PD), we have the required medical support and expertise and a new public dataset,
which enables us to design an end-to-end neural architecture … neurodegenerative diseases…

… machine learning architecture empowered with fuzzy-based decision level fusion medical
expert system is proposed for the prediction of heart disease. The proposed architecture …

… and crop disease prediction using deep learning architectures. … attention layer based
convolutional learning (DAL_CL) in … been classified using recursive architecture based on neural …

… Accordingly, this research considers cloud-based heart disease prediction using ML …
Ghazali, “Enhanced accuracy of heart disease prediction using machine learning and recurrent …

… that we implemented when using physical examination records to predict chronic diseases.
There are two different implementations of the DNN used for multi-label classification: one for …

… -task framework for disease onset prediction that combines … of different deep learning
architectures including CNN, LSTM … prediction models, our approach does not require disease …

… [50] built a graph-based attention model, capable of using hierarchical information inherent
to medical ontologies, resulting in a 10% higher accuracy for predicting rare diseases and 3…

… This paper proposes a novel deep learning architecture using a 1D convolutional neural …
reduce the limitations of classical machine learning approach. Several clinical parameters are …

… While the architectures are being trained in a distinct domain, we demonstrated that pre-…
The architecture of Inception is a variant of Google’s built deep learning architecture. There have …

… This article introduces some basic deep learning frameworks and some common diseases,
and summarizes the deep learning prediction methods corresponding to different diseases. …