Main objectives

The scope of ArtIPred project is to design and validate a smart health

system based on artificial intelligence (AI) as a predictor for chronic

kidney disease development using ECG signals from animal models.

The main advantage of this model is the fact that it will provide a safe

non-invasive way for patients to determine the state of their kidneys.

The proposed architecture implementing the ArtiPred system. With the

use of a wireless sensor we can capture ECG signals that will be further

processed amongst with other clinical data acquired with medical

equipment. The goal is to establish a clinical framework which will be

the basis of the CKD models development. In order to capture the

clinical data we will deploy a web interface which will allow to register

and store the clinical observation of the medical personnel, based on

imagistics and biochemistry trials. After establishing the clinical

framework and achieve the CKD data models, we will study and

experiment specific AI solutions in order to identify the correlations

between the ECG data sets and the disease evolution. The main goal is

to develop and validate, at laboratory level, an artificial intelligence

tool which will allow early diagnosis of the CKD.