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.