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Poster abstract: Detecting lung diseases with electrical impedance tomography

Year: 2024

Type: conference-paper

Abstract: 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.

Source: ACM Conference on Embedded Networked Sensor Systems (SenSys)

DOI: 10.1145/3666025.3699385

Authors: Barbara Stefaniak, Dariusz Wójcik, Tomasz Rymarczyk

Institution: University of Economics and Innovation

Language: English

Topic: Electrical and Bioimpedance Tomography

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

OpenAlex ID: W4404034515

FWCI:

Cites: 2

Cited by:

Related to: 10