Poster abstract: Detecting lung diseases with electrical impedance tomography

This paper presents novel diagnostic system for medicine, based on electrical impedance tomography (EIT). One of the primary functional features of this system is its ability to detect respiratory diseases with high accuracy, particularly focusing on conditions such as Chronic Obstructive Pulmonary Disease (COPD), Acute Respiratory Distress Syndrome (ARDS), Pneumothorax (PTX), Pulmonary Hypertension (PHTN), Pneumonia (PNA), and bronchospasm. A comparison of several classification models is presented, with the best-performing model achieving an accuracy rate of 98.22% in distinguishing between healthy and diseased patients.