APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS FOR MEDICAL DIAGNOSTICS AND PROGNOSTICS

4^th International Conference on Medical Informatics & Telehealth

October 6-7, 2016 | London, UK

Jaouher Ben Ali

university of Sousse, Tunisia

Posters & Accepted Abstracts: J Health Med Informat

Abstract :

In the medical field, diagnostic and prognostic remain the most important step to identify disease type and thereby define the adequate treatment before reaching catastrophic and fatal states. However, clinical symptoms and syndromes are not sufficient to detect some diseases. Consequently, the definition of new advanced techniques for medical diagnostics and prognostics are becoming of great interest to assist specialists in clinical researches and hence to ensure safety for millions of people. Artificial neural networks (ANNs) are inspired by the way that the brain performs computations: they are classified as one of the best and most used soft computing techniques. In this context, two innovative methods for early-stage Alzheimer�s disease diagnosis and blood glucose level prediction of Type 1 diabetes prediction and other cancer image analysis will be presented, as well as the result interpretation and some case studies. The aim of this work is to show the great assistance provided by these advanced techniques to the medical staff where the big data are processed through a trained ANNs leading accurate statistics leading suitable diagnostic decision making.

Biography :

Email: benalijaouher@yahoo.fr